Logo: to the web site of Uppsala University

uu.sePublications from Uppsala University
Change search
Refine search result
1234567 1 - 50 of 828
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Abdalmoaty, Mohamed
    KTH, Reglerteknik.
    Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.

    The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.

    In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.

  • 2.
    Abdalmoaty, Mohamed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    On Re-Weighting, Regularization Selection, and Transient in Nuclear Norm Based Identification2015In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 48, no 28, p. 92-97Article in journal (Refereed)
    Abstract [en]

    In this contribution, we consider the classical problem of estimating an Output Error model given a set of input-output measurements. First, we develop a regularization method based on the re-weighted nuclear norm heuristic. We show that the re-weighting improves the estimate in terms of better fit. Second, we suggest an implementation method that helps in eliminating the regularization parameters from the problem by introducing a constant based on a validation criterion. Finally, we develop a method for considering the effect of the transient when the initial conditions are unknown. A simple numerical example is used to demonstrate the proposed method in comparison to classical and another recent method based on the nuclear norm heuristic.

  • 3.
    Abdalmoaty, Mohamed
    et al.
    Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden.
    Hjalmarsson, Håkan
    Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden.
    Wahlberg, Bo
    Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden.
    The Gaussian MLE versus the Optimally weighted LSE2020In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 37, no 6, p. 195-199Article in journal (Refereed)
    Abstract [en]

    In this note, we derive and compare the asymptotic covariance matrices of two parametric estimators: the Gaussian Maximum Likelihood Estimator (MLE), and the optimally weighted Least-Squares Estimator (LSE). We assume a general model parameterization where the model's mean and variance are jointly parameterized, and consider Gaussian and non-Gaussian data distributions.

  • 4.
    Abdalmoaty, Mohamed
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Noise reduction in Laguerre-domain discrete delay estimation2022In: 2022 IEEE 61st Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 6254-6259Conference paper (Refereed)
    Abstract [en]

    This paper introduces a stochastic framework for a recently proposed discrete-time delay estimation method in Laguerre-domain, i.e. with the delay block input and output signals being represented by the corresponding Laguerre series. A novel Laguerre-domain disturbance model allowing the involved signals to be square-summable sequences is devised. The relation to two commonly used time-domain disturbance models is clarified. Furthermore, by forming the input signal in a certain way, the signal shape of an additive output disturbance can be estimated and utilized for noise reduction. It is demonstrated that a significant improvement in the delay estimation error is achieved when the noise sequence is correlated. The noise reduction approach is applicable to other Laguerre-domain problems than pure delay estimation.

  • 5.
    Abdalmoaty, Mohamed R. H.
    et al.
    KTH, Reglerteknik.
    Rojas, Cristian R.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Identification of a Class of Nonlinear Dynamical Networks2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 868-873Article in journal (Refereed)
    Abstract [en]

    Identifcation of dynamic networks has attracted considerable interest recently. So far the main focus has been on linear time-invariant networks. Meanwhile, most real-life systems exhibit nonlinear behaviors; consider, for example, two stochastic linear time-invariant systems connected in series, each of which has a nonlinearity at its output. The estimation problem in this case is recognized to be challenging, due to the analytical intractability of both the likelihood function and the optimal one-step ahead predictors of the measured nodes. In this contribution, we introduce a relatively simple prediction error method that may be used for the estimation of nonlinear dynamical networks. The estimator is defined using a deterministic predictor that is nonlinear in the known signals. The estimation problem can be defined using closed-form analytical expressions in several non-trivial cases, and Monte Carlo approximations are not necessarily required. We show, that this is the case for some block-oriented networks with no feedback loops and where all the nonlinear modules are polynomials. Consequently, the proposed method can be applied in situations considered challenging by current approaches. The performance of the estimation method is illustrated on a numerical simulation example.

  • 6.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems2016In: 2016 IEEE 55th Conference on Decision and Control (CDC), IEEE, 2016, p. 3060-3065Conference paper (Refereed)
    Abstract [en]

    This paper introduces a simulation-based method for maximum likelihood estimation of stochastic Wienersystems. It is well known that the likelihood function ofthe observed outputs for the general class of stochasticWiener systems is analytically intractable. However, when the distributions of the process disturbance and the measurement noise are available, the likelihood can be approximated byrunning a Monte-Carlo simulation on the model. We suggest the use of Laplace importance sampling techniques for the likelihood approximation. The algorithm is tested on a simple first order linear example which is excited only by the process disturbance. Further, we demonstrate the algorithm on an FIR system with cubic nonlinearity. The performance of the algorithm is compared to the maximum likelihood method and other recent techniques.

  • 7.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 784-789Article in journal (Refereed)
    Abstract [en]

    The estimation problem of stochastic Wiener-Hammerstein models is recognized to be challenging, mainly due to the analytical intractability of the likelihood function. In this contribution, we apply a computationally attractive prediction error method estimator to a real-data stochastic Wiener-Hammerstein benchmark problem. The estimator is defined using a deterministic predictor that is nonlinear in the input. The prediction error method results in tractable expressions, and Monte Carlo approximations are not necessary. This allows us to tackle several issues considered challenging from the perspective of the current mainstream approach. Under mild conditions, the estimator can be shown to be consistent and asymptotically normal. The results of the method applied to the benchmark data are presented and discussed.

  • 8.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors2018In: 2018 IEEE Conference on Decision and Control (CDC), IEEE, 2018, p. 3842-3847Conference paper (Refereed)
    Abstract [en]

    We consider a parameter estimation problem in a general class of stochastic multiple-inputs multiple-outputs Wiener models, where the likelihood function is, in general, analytically intractable. When the output signal is a scalar independent stochastic process, the likelihood function of the parameters is given by a product of scalar integrals. In this case, numerical integration may be efficiently used to approximately solve the maximum likelihood problem. Otherwise, the likelihood function is given by a challenging multidimensional integral. In this contribution, we argue that by ignoring the temporal and spatial dependence of the stochastic disturbances, a computationally attractive estimator based on a suboptimal predictor can be constructed by evaluating scalar integrals regardless of the number of outputs. Under some conditions, the convergence of the resulting estimators can be established and consistency is achieved under certain identifiability hypothesis. We highlight the relationship between the resulting estimators and a recently proposed prediction error method estimator. We also remark that the method can be used for a wider class of stochastic nonlinear models. The performance of the method is demonstrated by a numerical simulation example using a 2-inputs 2-outputs model with 9 parameters.

  • 9.
    Abdalmoaty, Mohamed Rasheed
    et al.
    KTH, Reglerteknik.
    Hjalmarsson, Håkan
    KTH, Reglerteknik.
    Simulated Pseudo Maximum Likelihood Identification of Nonlinear Models2017In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 50, no 1, p. 14058-14063Article in journal (Refereed)
    Abstract [en]

    Nonlinear stochastic parametric models are widely used in various fields. However, for these models, the problem of maximum likelihood identification is very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the analytically intractable likelihood function and compute either the maximum likelihood or a Bayesian estimator. These methods, albeit asymptotically optimal, are computationally expensive. In this contribution, we present a simulation-based pseudo likelihood estimator for nonlinear stochastic models. It relies only on the first two moments of the model, which are easy to approximate using Monte-Carlo simulations on the model. The resulting estimator is consistent and asymptotically normal. We show that the pseudo maximum likelihood estimator, based on a multivariate normal family, solves a prediction error minimization problem using a parameterized norm and an implicit linear predictor. In the light of this interpretation, we compare with the predictor defined by an ensemble Kalman filter. Although not identical, simulations indicate a close relationship. The performance of the simulated pseudo maximum likelihood method is illustrated in three examples. They include a challenging state-space model of dimension 100 with one output and 2 unknown parameters, as well as an application-motivated model with 5 states, 2 outputs and 5 unknown parameters.

  • 10.
    Abd-Elrady, Emad
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Harmonic signal modeling based on the Wiener model structure2002Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The estimation of frequencies and corresponding harmonic overtones is a problem of great importance in many situations. Applications can, for example, be found in supervision of electrical power transmission lines, in seismology and in acoustics. Generally, a periodic function with an unknown fundamental frequency in cascade with a parameterized and unknown nonlinear function can be used as a signal model for an arbitrary periodic signal. The main objective of the proposed modeling technique is to estimate the fundamental frequency of the periodic function in addition to the parameters of the nonlinear function.

    The thesis is divided into four parts. In the first part, a general introduction to the harmonic signal modeling problem and different approaches to solve the problem are given. Also, an outline of the thesis and future research topics are introduced.

    In the second part, a previously suggested recursive prediction error method (RPEM) for harmonic signal modeling is studied by numerical examples to explore the ability of the algorithm to converge to the true parameter vector. Also, the algorithm is modified to increase its ability to track the fundamental frequency variations.

    A modified algorithm is introduced in the third part to give the algorithm of the second part a more stable performance. The modifications in the RPEM are obtained by introducing an interval in the nonlinear block with fixed static gain. The modifications that result in the convergence analysis are, however, substantial and allows a complete treatment of the local convergence properties of the algorithm. Moreover, the Cramér–Rao bound (CRB) is derived for the modified algorithm and numerical simulations indicate that the method gives good results especially for moderate signal to noise ratios (SNR).

    In the fourth part, the idea is to give the algorithm of the third part the ability to estimate the driving frequency and the parameters of the nonlinear output function parameterized also in a number of adaptively estimated grid points. Allowing the algorithm to automatically adapt the grid points as well as the parameters of the nonlinear block, reduces the modeling errors and gives the algorithm more freedom to choose the suitable grid points. Numerical simulations indicate that the algorithm converges to the true parameter vector and gives better performance than the fixed grid point technique. Also, the CRB is derived for the adaptive grid point technique.

    Download full text (ps)
    fulltext
  • 11.
    Abd-Elrady, Emad
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Nonlinear Approaches to Periodic Signal Modeling2005Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Periodic signal modeling plays an important role in different fields. The unifying theme of this thesis is using nonlinear techniques to model periodic signals. The suggested techniques utilize the user pre-knowledge about the signal waveform. This gives these techniques an advantage as compared to others that do not consider such priors.

    The technique of Part I relies on the fact that a sine wave that is passed through a static nonlinear function produces a harmonic spectrum of overtones. Consequently, the estimated signal model can be parameterized as a known periodic function (with unknown frequency) in cascade with an unknown static nonlinearity. The unknown frequency and the parameters of the static nonlinearity are estimated simultaneously using the recursive prediction error method (RPEM). A treatment of the local convergence properties of the RPEM is provided. Also, an adaptive grid point algorithm is introduced to estimate the unknown frequency and the parameters of the static nonlinearity in a number of adaptively estimated grid points. This gives the RPEM more freedom to select the grid points and hence reduces modeling errors.

    Limit cycle oscillations problem are encountered in many applications. Therefore, mathematical modeling of limit cycles becomes an essential topic that helps to better understand and/or to avoid limit cycle oscillations in different fields. In Part II, a second-order nonlinear ODE is used to model the periodic signal as a limit cycle oscillation. The right hand side of the ODE model is parameterized using a polynomial function in the states, and then discretized to allow for the implementation of different identification algorithms. Hence, it is possible to obtain highly accurate models by only estimating a few parameters.

    In Part III, different user aspects for the two nonlinear approaches of the thesis are discussed. Finally, topics for future research are presented.

    Download full text (pdf)
    FULLTEXT01
  • 12.
    Abd-Elrady, Emad
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Periodic signal analysis using orbits of nonlinear ODEs based on the Markov estimate2004Conference paper (Refereed)
  • 13.
    Abd-Elrady, Emad
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Periodic signal modeling based on Liénard's equation2004In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 49, no 10, p. 1773-1778Article in journal (Refereed)
  • 14.
    Abd-Elrady, Emad
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Söderström, Torsten
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Periodic signal modeling based on Liénard's equation2003Report (Other academic)
    Download full text (pdf)
    fulltext
  • 15.
    Abrahamsson, Richard
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Estimation Problems in Array Signal Processing, System Identification, and Radar Imagery2006Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This thesis is concerned with parameter estimation, signal processing, and applications.

    In the first part, imaging using radar is considered. More specifically, two methods are presented for estimation and removal of ground-surface reflections in ground penetrating radar which otherwise hinder reliable detection of shallowly buried landmines. Further, a study of two autofocus methods for synthetic aperture radar is presented. In particular, we study their behavior in scenarios where the phase errors leading to cross-range defocusing are of a spatially variant kind.

    In the subsequent part, array signal processing and optimal beamforming is regarded. In particular, the phenomenon of signal cancellation in adaptive beamformers due to array perturbations, signal correlated interferences and limited data for covariance matrix estimation is considered. For the general signal cancellation problem, a class of improved adaptive beamformers is suggested based on ridge-regression. Another set of methods is suggested to mitigate signal cancellation due to correlated signal and interferences based on a novel way of finding a characterization of the interference subspace from observed array data. Further, a new minimum variance beamformer is presented for high resolution non-parametric spatial spectrum estimation in cases where the impinging signals are correlated. Lastly, a multitude of enhanced covariance matrix estimators from the statistical literature are studied as an alternative to other robust adaptive beamforming methods. The methods are also applied to space-time adaptive processing where limited data for covariance matrix estimation is a common problem.

    In the third and final part the estimation of the parameters of a general bilinear problem is considered. The bilinear model is motivated by the application of identifying submarines from their electromagnetic signature and by the identification of a Hamerstein-Wiener model of a non-linear dynamic system. An efficient approximate maximum-likelihood method with closed form solution is suggested for estimating the bilinear model parameters.

  • 16.
    Abuzohri, Ahmed
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
    Effektförstärkare med strömkontroll2012Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Energin är ett begrepp som används dagligen i vårt samhälle. Energin kan inte skapas men däremot kan den omvandlas till olika former, förbrukas och lagras i vissa fall. Men att omvandla energi från en form till en annan form för att sedan lagra den är en av dagens stora utmaningar inom tekniken då vi måste följa de regler som naturen dikterar. Forskning på detta område har pågått i flera decennier för att kunna ta fram lämpliga och effektiva sätt att lagra energi på. Svänghjul-system är ett sådant sätt där man kan lagra energi under begränsad tid.

    I mitt examensarbete har jag utnyttjat kunskapen som jag har lärt mig från elektronik kurserna för att konstruera en effektförstärkare med strömkontroll som användes för att driva ett svänghjul-system. Förstärkaren har byggts med elektronikkomponenter och styrs från datorn med m.h.a. styrprogrammet LabVIEW som kommunicerar med hårdvaran och kontrollerar svänghjulets rörelse.

    Download full text (pdf)
    fulltext
  • 17.
    af Ekenstam, Love
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Modellering av signalbehandlingen i ett cochleaimplantat och utvärdering av modellen.2014Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A program that simulates the signal processing in a cochlear implant using the signal processing strategy ACE (Advanced Combination Encoder) was constructed. Its main purpose is to, in advance, predict and test different implant settings with the purpose to be able to predict individual patient's differences in implant settings.

     

    The program was validated using output signals processed by Cochlear Limited using their own Matlab Toolbox for implant research, NMT (Nucleus Matlab Toolbox). Identical signals were processed by the program and then compared with NMT:s output. The outputs, produced with several different identical settings matched each other well.

     

    The amplitude compression function, a vital part of the signal processing, also matched well, apart from a relative loss of strength at high input amplitudes. The program will now be used by the cochlear implant section at Uppsala University Hospital to try out individual settings for cochlear implant users. The hope for the future is that better implant settings will lead to improved speech and sound experience, especially, in the long run, with regards to music.

    Download full text (pdf)
    fulltext
  • 18.
    Afzalan, Bakhtiar
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering.
    Detection of voids in welded joints using ultrasonic inspection: Quality control of welded joints in copper canisters for purpose of permanent storage of used nuclear waste2021Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis was done i cooperation with SKB Clab in Oskarshamn and studies use of sonic waves for detecting voids and irregularities in the weld joints of copper capsules used for long term storage of radioactive waste. Since these could pose material failure and thereby risk radioactive contamination of ground water it is very important to find means of quality control before storage. 

    During the welding procedure changes occur to the integrity of the material. The homogenous metal – in this case copper – is distorted and voids appear in and around the welded volume. A non-destructive inspection method is needed to make sure that the metal holds for the strains of long term storage. These strains are not completely known at the moment and therefore the goal of this thesis is mainly to add another tool of inspection for future studies.

    The tests are done using ultrasonic mapping of the welded volume. This is achieved by sending ultrasonic pulse through test samples – welded copper pieces – and recording its reflection. The recorded signals are gathered in data matrices and processed using several different signal processing methods in search of irregularities and voids. To enhance the understanding of the results a graphical user interface (GUI) is developed that allows users to visualize the results. 

    The welded pieces, the ultrasonic mapping and its resulting data sets were delivered to this thesis and the scope of the thesis is to develop the GUI and apply known signal processing methods to the data set. 

    It is shown that the irregularities do appear and that ultrasonic detection and use of the processing method is useful for quality control of the material. Further field studies are needed to identify maximum number, size and perhaps shapes of irregularities that can be within tolerance levels of the storage project. 

     

    Download full text (pdf)
    fulltext
  • 19. Ahlgren Peters, Adam
    et al.
    Söderholm, Robin
    Wahlmark, Rickard
    Analog gitarrförstärkare: med rörliknande egenskaper2017Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Download full text (pdf)
    fulltext
  • 20.
    Ahlén, A
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Lindbom, L
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, M
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Analysis of stability and performance of adaptation algorithms with time-invariant gains2004In: IEEE Transactions on Signal Processing, Vol. 52, p. 103-116Article in journal (Refereed)
  • 21.
    Ahlén, A
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Materials Science. SIGNALS AND SYSTEMS.
    Sternad, M
    Lindbom, L
    Iterative Wiener design of adaptation laws with constant gains2001In: IEEE International Conference on Acoustics, Speech and Signal Processing, Salt Lake City, UT, 2001Conference paper (Refereed)
  • 22.
    Aitman, Victor
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Signals and Systems.
    Conductive interferences from multiple EC-motor installation: To measure and mitigate harmonics2022Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Products produced by a Swedish company are requested to be investigated regarding their harmonic and inter-harmonic currents injected into the public supply system to comply with the Swedish standard SS-EN IEC 61000-3-2, Electromagnetic compatibility (EMC).   

    On behalf of Systemair Sweden AB, this bachelor thesis aims firstly to investigate if their product, PAFEC 4225 WH (Air Curtain), complies with standard SS-EN IEC 61000-3-2, and if not, what measures should be taken; and secondly to develop a low-cost instrument for the measurement of harmonics and inter-harmonics according to standard IEC 61000-4-7 related to the requirements on equipment used in standard SS-EN IEC 61000-3-2.

    To this purpose, the standards have been looked into thoroughly, the preconditions for measurements have been studied in detail, and external meetings with a consultant at Delta Development Technology AB have been performed. Measurements of the harmonic spectrum generated by PAFEC 4225 WH have been performed first at Systemair Sweden AB’s Technical center in Skinnskatteberg, and later at Delta Development in Västerås. After this, a low-cost instrument was developed, including hardware and software design and implementation. The hardware implementation consists of a circuit board designed using EasyEDA (an online PCB Design Tool), a NI myDAQ (a data acquisition device made by National Instruments), and an enclosure designed with Solidworks and made with a 3D-printer. The software implementation was conducted using LabVIEW – a graphical programming language. 

    A few measurements were performed using instruments complying IEC 61000-4-7 at Delta Development, and later with the low-cost instrument. Different line chokes were measured. The results showed that a 15 mH line choke connected in series with each motor would make the PAFEC 4225 WH comply with SS-EN IEC 61000-3-2. The results from the low-cost instrument did not match Delta Developments results regarding harmonic and inter-harmonic content. The difference could be caused by unfinished algorithm, different measurements conditions, and missing anti-aliasing-filter.         

    For the future work it is recommended that Systemair Sweden AB can either develop the low-cost instrument or buy an existing instrument that complies with IEC 61000-4-7, to enable to do measurements that comply with SS-EN IEC 61000-3-2. One does also need to investigate the grid during low activity or consider buying a signal generator for the purpose of fulfilling the preconditions to enable measurements. It is also recommended that further measurements are performed with the proposed line choke installed to check for any change in performance of the product. 

    Download full text (pdf)
    fulltext
  • 23.
    Alavanja, Bojan
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Application of SCADA Data Monitoring Methodology and Reliability Analysis of Wind Farm Operational Data2016Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Reliability of wind turbine components and maintenance optimisation are among the critical aspects of wind power development closely related to profitability and future development. The main reason for research in these areas is lowering the cost of energy production for wind power, specifically important in offshore environment. Continuous monitoring of specific wind turbine components can be valuable for wind farm operators and, subsequently, wind farm owners.  Also, health assessment of critical components can be useful in estimating the possibilities for life extension of wind turbines. Expensive Condition Monitoring Systems (CMSs) are not always available, particularly in older wind farms, and additionally installing CMSs on wind turbines is not always economically feasible. However, most of modern wind turbines are equipped with the Supervisory Control And Data Acquisition (SCADA) system which is recording 10-minute average values of parameters that depict operation of the turbine. That being said, SCADA data contains a vast amount of information that can be used for analysis of wind turbine components health. Therefore, this project will present an application of previously published methodology for SCADA data condition monitoring on real wind farm data. The goal of this project is to investigate on the possibilities of the SCADA monitoring methodology and what can be the added value of the application for wind farm operators, owners and other stakeholders.

    The methodology for condition monitoring through SCADA data was applied on real data gathered from two wind farms in Germany and one in the Netherlands. During the project the methodology had to be modified in order to ensure the best possible industrial application. Results of the project showed that the SCADA data condition monitoring approach is not capable of predicting failures. However, the technique has been proven successful for detecting the changes of trends in dependencies of working parameters, specifically monitoring parameters related to the turbine generators. Continuously monitoring the dependencies of working parameters can be used as an additional source of information for maintenance scheduling and assessment of components health. The approach presented in this paper can be valuable to asset managers and wind farm owners.

    Download full text (pdf)
    fulltext
  • 24.
    Alenlöv, Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Olsson, Jimmy
    Particle-based adaptive-lag online marginal smoothing in general state-space models2019In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, no 21, p. 5571-5582Article in journal (Refereed)
  • 25.
    Alfredsson, Stefan
    et al.
    Karlstad universitet.
    Brunström, Anna
    Karlstad universitet.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Impact of 4G wireless link configurations on VoIP network performance2008In: IEEE International Symposium on Wireless Communication Systems 2008, ISWCS2008, Reykjavik, Iceland, 2008Conference paper (Refereed)
  • 26.
    Ambrozinski, Lukasz
    et al.
    Department of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Kraków, Polen.
    Packo, Pawel
    Department of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Kraków, Polen.
    Stepinski, Tadeusz
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Uhl, Tadeusz
    Department of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Kraków, Polen.
    Ultrasonic guided waves based method for SHM: Simulations and an experimental test2011In: 5th World Conference on Structural Control and Monitoring, Tokyo, Japan, 2011Conference paper (Refereed)
  • 27.
    Ambrozinski, Lukasz
    et al.
    AGH University of Science and Technology, Kraków, Polen.
    Stepinski, Tadeusz
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Packo, Pawel
    AGH University of Science and Technology, Kraków, Polen.
    Uhl, Tadeusz
    AGH University of Science and Technology, Kraków, Polen.
    Self-focusing Lamb waves based on the decomposition of the time-reversal operator using time-frequency representation2012In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 27, p. 337-349Article in journal (Refereed)
    Abstract [en]

    Active ultrasonic arrays are very useful for structural health monitoring (SHM) of large plate-like structures. Large areas of a plate can be monitored from a fixed position but it normally requires precise information on material properties. Self-focusing methods can perform well without the exact knowledge of a medium and array parameters. In this paper a method for selective focusing of Lamb waves will be presented. The algorithm is an extension of the DORT method (French acronym for decomposition of time-reversal operator) where the continuous wavelet transform (CWT) is used for the time-frequency representation (TFR) of nonstationary signals instead of the discrete Fourier transform. The performance of the methods is compared and verified in the paper using both simulated and experimental data. It is shown that the extension of the DORT method with the use of TFR considerably improved its resolving ability. To experimentally evaluate the performance of the proposed method, a linear array of small piezoelectric transducers attached to an aluminum plate was used to obtain interelement responses, required for beam self-focusing on targets present in the plate. The array was used for the transmission of signals calculated with the DORT-CWT algorithm. To verify the self-focusing effect the backpropagated field generated in the experiment was sensed using laser scanning vibrometer.

  • 28.
    Ambrozinski, Lukasz
    et al.
    AGH University of Science and Technology, Kraków, Polen.
    Stepinski, Tadeusz
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Uhl, Tadeusz
    AGH University of Science and Technology, Kraków, Polen.
    Self focusing of 2D arrays for SHM of plate-like structures using time reversal operator2011In: 8th Workshop on SHM, Stanford, CA, 2011, 2011Conference paper (Refereed)
  • 29. Ancuti, Codruta O.
    et al.
    Luo, Ziwei
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Gustafsson, Fredrik K.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Zhao, Zheng
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Sjölund, Jens
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Schön, Thomas B.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Busch, Christoph
    NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report2023In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancover: Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper (Refereed)
    Abstract [en]

    This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams that competed in the final testing phase, and the proposed solutions demonstrated the cutting-edge in image dehazing technology.

  • 30.
    Andersson, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Deep learning applied to system identification: A probabilistic approach2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Machine learning has been applied to sequential data for a long time in the field of system identification. As deep learning grew under the late 00's machine learning was again applied to sequential data but from a new angle, not utilizing much of the knowledge from system identification. Likewise, the field of system identification has yet to adopt many of the recent advancements in deep learning. This thesis is a response to that. It introduces the field of deep learning in a probabilistic machine learning setting for problems known from system identification.

    Our goal for sequential modeling within the scope of this thesis is to obtain a model with good predictive and/or generative capabilities. The motivation behind this is that such a model can then be used in other areas, such as control or reinforcement learning. The model could also be used as a stepping stone for machine learning problems or for pure recreational purposes.

    Paper I and Paper II focus on how to apply deep learning to common system identification problems. Paper I introduces a novel way of regularizing the impulse response estimator for a system. In contrast to previous methods using Gaussian processes for this regularization we propose to parameterize the regularization with a neural network and train this using a large dataset. Paper II introduces deep learning and many of its core concepts for a system identification audience. In the paper we also evaluate several contemporary deep learning models on standard system identification benchmarks. Paper III is the odd fish in the collection in that it focuses on the mathematical formulation and evaluation of calibration in classification especially for deep neural network. The paper proposes a new formalized notation for calibration and some novel ideas for evaluation of calibration. It also provides some experimental results on calibration evaluation.

    List of papers
    1. Data-driven impulse response regularization via deep learning
    Open this publication in new window or tab >>Data-driven impulse response regularization via deep learning
    2018 (English)Conference paper, Published paper (Refereed)
    Series
    IFAC-PapersOnLine, ISSN 2405-8963 ; 51:15
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-366186 (URN)10.1016/j.ifacol.2018.09.081 (DOI)000446599200002 ()
    Conference
    SYSID 2018, July 9–11, Stockholm, Sweden
    Available from: 2018-10-08 Created: 2018-11-22 Last updated: 2022-04-04Bibliographically approved
    2. Deep convolutional networks in system identification
    Open this publication in new window or tab >>Deep convolutional networks in system identification
    Show others...
    2019 (English)In: Proc. 58th IEEE Conference on Decision and Control, IEEE, 2019, p. 3670-3676Conference paper, Published paper (Refereed)
    Abstract [en]

    Recent developments within deep learning are relevant for nonlinear system identification problems. In this paper, we establish connections between the deep learning and the system identification communities. It has recently been shown that convolutional architectures are at least as capable as recurrent architectures when it comes to sequence modeling tasks. Inspired by these results we explore the explicit relationships between the recently proposed temporal convolutional network (TCN) and two classic system identification model structures; Volterra series and block-oriented models. We end the paper with an experimental study where we provide results on two real-world problems, the well-known Silverbox dataset and a newer dataset originating from ground vibration experiments on an F-16 fighter aircraft.

    Place, publisher, year, edition, pages
    IEEE, 2019
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:uu:diva-397528 (URN)10.1109/CDC40024.2019.9030219 (DOI)000560779003058 ()978-1-7281-1398-2 (ISBN)
    Conference
    CDC 2019, December 11–13, Nice, France
    Funder
    Swedish Foundation for Strategic Research , RIT15-0012Swedish Research Council, 621-2016-06079
    Available from: 2020-03-12 Created: 2019-11-21 Last updated: 2022-04-04Bibliographically approved
    3. Evaluating model calibration in classification
    Open this publication in new window or tab >>Evaluating model calibration in classification
    Show others...
    2019 (English)In: 22nd International Conference on Artificial Intelligence and Statistics, 2019, p. 3459-3467Conference paper, Published paper (Refereed)
    Series
    Proceedings of Machine Learning Research, ISSN 2640-3498 ; 89
    National Category
    Probability Theory and Statistics
    Identifiers
    urn:nbn:se:uu:diva-397519 (URN)000509687903053 ()
    Conference
    AISTATS 2019, April 16–18, Naha, Japan
    Available from: 2019-04-25 Created: 2019-11-21 Last updated: 2023-04-26Bibliographically approved
    Download full text (pdf)
    fulltext
  • 31.
    Andersson, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Deep probabilistic models for sequential and hierarchical data2022Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Consider the problem where we want a computer program capable of recognizing a pedestrian on the road. This could be employed in a car to automatically apply the brakes to avoid an accident. Writing such a program is immensely difficult but what if we could instead use examples and let the program learn what characterizes a pedestrian from the examples. Machine learning can be described as the process of teaching a model (computer program) to predict something (the presence of a pedestrian) with help of data (examples) instead of through explicit programming.

    This thesis focuses on a specific method in machine learning, called deep learning. This method can arguably be seen as sole responsible for the recent upswing of machine learning in academia as well as in society at large. However, deep learning requires, in human standards, a huge amount of data to perform well which can be a limiting factor.  In this thesis we describe different approaches to reduce the amount of data that is needed by encoding some of our prior knowledge about the problem into the model. To this end we focus on sequential and hierarchical data, such as speech and written language.

    Representing sequential output is in general difficult due to the complexity of the output space. Here, we make use of a probabilistic approach focusing on sequential models in combination with a deep learning structure called the variational autoencoder. This is applied to a range of different problem settings, from system identification to speech modeling.

    The results come in three parts. The first contribution focus on applications of deep learning to typical system identification problems, the intersection between the two areas and how they can benefit from each other. The second contribution is on hierarchical data where we promote a multiscale variational autoencoder inspired by image modeling. The final contribution is on verification of probabilistic models, in particular how to evaluate the validity of a probabilistic output, also known as calibration.

    List of papers
    1. Data-driven impulse response regularization via deep learning
    Open this publication in new window or tab >>Data-driven impulse response regularization via deep learning
    2018 (English)Conference paper, Published paper (Refereed)
    Series
    IFAC-PapersOnLine, ISSN 2405-8963 ; 51:15
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-366186 (URN)10.1016/j.ifacol.2018.09.081 (DOI)000446599200002 ()
    Conference
    SYSID 2018, July 9–11, Stockholm, Sweden
    Available from: 2018-10-08 Created: 2018-11-22 Last updated: 2022-04-04Bibliographically approved
    2. Deep convolutional networks in system identification
    Open this publication in new window or tab >>Deep convolutional networks in system identification
    Show others...
    2019 (English)In: Proc. 58th IEEE Conference on Decision and Control, IEEE, 2019, p. 3670-3676Conference paper, Published paper (Refereed)
    Abstract [en]

    Recent developments within deep learning are relevant for nonlinear system identification problems. In this paper, we establish connections between the deep learning and the system identification communities. It has recently been shown that convolutional architectures are at least as capable as recurrent architectures when it comes to sequence modeling tasks. Inspired by these results we explore the explicit relationships between the recently proposed temporal convolutional network (TCN) and two classic system identification model structures; Volterra series and block-oriented models. We end the paper with an experimental study where we provide results on two real-world problems, the well-known Silverbox dataset and a newer dataset originating from ground vibration experiments on an F-16 fighter aircraft.

    Place, publisher, year, edition, pages
    IEEE, 2019
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:uu:diva-397528 (URN)10.1109/CDC40024.2019.9030219 (DOI)000560779003058 ()978-1-7281-1398-2 (ISBN)
    Conference
    CDC 2019, December 11–13, Nice, France
    Funder
    Swedish Foundation for Strategic Research , RIT15-0012Swedish Research Council, 621-2016-06079
    Available from: 2020-03-12 Created: 2019-11-21 Last updated: 2022-04-04Bibliographically approved
    3. Learning deep autoregressive models for hierarchical data
    Open this publication in new window or tab >>Learning deep autoregressive models for hierarchical data
    2021 (English)In: IFAC PapersOnLine, Elsevier BV Elsevier, 2021, Vol. 54, no 7, p. 529-534Conference paper, Published paper (Refereed)
    Abstract [en]

    We propose a model for hierarchical structured data as an extension to the stochastic temporal convolutional network. The proposed model combines an autoregressive model with a hierarchical variational autoencoder and downsampling to achieve superior computational complexity. We evaluate the proposed model on two different types of sequential data: speech and handwritten text. The results are promising with the proposed model achieving state-of-the-art performance.

    Place, publisher, year, edition, pages
    ElsevierElsevier BV, 2021
    Keywords
    Deep learning, variational autoencoders, nonlinear systems
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Identifiers
    urn:nbn:se:uu:diva-457738 (URN)10.1016/j.ifacol.2021.08.414 (DOI)000696396200091 ()
    Conference
    19th IFAC Symposium on System Identification (SYSID), JUL 13-16, 2021, Padova, ITALY
    Funder
    Swedish Research CouncilKjell and Marta Beijer Foundation
    Available from: 2021-11-12 Created: 2021-11-12 Last updated: 2024-01-15Bibliographically approved
    4. Evaluating model calibration in classification
    Open this publication in new window or tab >>Evaluating model calibration in classification
    Show others...
    2019 (English)In: 22nd International Conference on Artificial Intelligence and Statistics, 2019, p. 3459-3467Conference paper, Published paper (Refereed)
    Series
    Proceedings of Machine Learning Research, ISSN 2640-3498 ; 89
    National Category
    Probability Theory and Statistics
    Identifiers
    urn:nbn:se:uu:diva-397519 (URN)000509687903053 ()
    Conference
    AISTATS 2019, April 16–18, Naha, Japan
    Available from: 2019-04-25 Created: 2019-11-21 Last updated: 2023-04-26Bibliographically approved
    Download full text (pdf)
    UUThesis_Andersson,C_2022
    Download full text (pdf)
    UUThesis_Andersson,C_2022
    Download (jpg)
    presentationsbild
  • 32.
    Andersson, Carl
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wahlström, Niklas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Schön, Thomas B.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Data-driven impulse response regularization via deep learning2018Conference paper (Refereed)
  • 33.
    Andersson, Claes R.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology.
    Fryknäs, Mårten
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Rickardson, Linda
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology.
    Larsson, Rolf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology.
    Isaksson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology.
    Gustafsson, Mats G.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology. Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    In vitro drug sensitivity-gene expression correlations involve a tissue of origin dependency2007In: Journal of chemical information and modeling, ISSN 1549-9596, Vol. 47, no 1, p. 239-248Article in journal (Refereed)
    Abstract [en]

    A major concern of chemogenomics is to associate drug activity with biological variables. Several reports have clustered cell line drug activity profiles as well as drug activity-gene expression correlation profiles and noted that the resulting groupings differ but still reflect mechanism of action. The present paper shows that these discrepancies can be viewed as a weighting of drug-drug distances, the weights depending on which cell lines the two drugs differ in.

  • 34.
    Andersson, Claes R.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Hvidsten, Torgeir R.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Isaksson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Gustafsson, Mats G.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology. Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Revealing cell cycle control by combining model-based detection of periodic expression with novel cis-regulatory descriptors2007In: BMC Systems Biology, E-ISSN 1752-0509, Vol. 1, p. 45-Article in journal (Refereed)
    Abstract [en]

    Background: We address the issue of explaining the presence or absence of phase-specific transcription in budding yeast cultures under different conditions. To this end we use a model-based detector of gene expression periodicity to divide genes into classes depending on their behavior in experiments using different synchronization methods. While computational inference of gene regulatory circuits typically relies on expression similarity (clustering) in order to find classes of potentially co-regulated genes, this method instead takes advantage of known time profile signatures related to the studied process. Results: We explain the regulatory mechanisms of the inferred periodic classes with cis-regulatory descriptors that combine upstream sequence motifs with experimentally determined binding of transcription factors. By systematic statistical analysis we show that periodic classes are best explained by combinations of descriptors rather than single descriptors, and that different combinations correspond to periodic expression in different classes. We also find evidence for additive regulation in that the combinations of cis-regulatory descriptors associated with genes periodically expressed in fewer conditions are frequently subsets of combinations associated with genes periodically expression in more conditions. Finally, we demonstrate that our approach retrieves combinations that are more specific towards known cell-cycle related regulators than the frequently used clustering approach. Conclusion: The results illustrate how a model-based approach to expression analysis may be particularly well suited to detect biologically relevant mechanisms. Our new approach makes it possible to provide more refined hypotheses about regulatory mechanisms of the cell cycle and it can easily be adjusted to reveal regulation of other, non-periodic, cellular processes.

  • 35. Andersson, Tobias
    et al.
    Sellergren, Albin
    Toft, Jonathan
    Signal processing through electroencephalography: Independent project in electrical engineering2016Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Download full text (pdf)
    Rapport
  • 36.
    Anubhab, Ghosh
    et al.
    KTH Royal Institute of Technology.
    Abdalmoaty, Mohamed
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Chatterjee, Saikat
    KTH Royal Institute of Technology.
    Hjalmarsson, Håkan
    KTH Royal Institute of Technology.
    DeepBayes -- an estimator for parameter estimation in stochastic nonlinear dynamical modelsManuscript (preprint) (Other academic)
    Abstract [en]

    Stochastic nonlinear dynamical systems are ubiquitous in modern, real-world applications. Yet, estimating the unknown parameters of stochastic, nonlinear dynamical models remains a challenging problem. The majority of existing methods employ maximum likelihood or Bayesian estimation. However, these methods suffer from some limitations, most notably the substantial computational time for inference coupled with limited flexibility in application. In this work, we propose DeepBayes estimators that leverage the power of deep recurrent neural networks in learning an estimator. The method consists of first training a recurrent neural network to minimize the mean-squared estimation error over a set of synthetically generated data using models drawn from the model set of interest. The a priori trained estimator can then be used directly for inference by evaluating the network with the estimation data. The deep recurrent neural network architectures can be trained offline and ensure significant time savings during inference. We experiment with two popular recurrent neural networks -- long short term memory network (LSTM) and gated recurrent unit (GRU). We demonstrate the applicability of our proposed method on different example models and perform detailed comparisons with state-of-the-art approaches. We also provide a study on a real-world nonlinear benchmark problem. The experimental evaluations show that the proposed approach is asymptotically as good as the Bayes estimator. 

  • 37.
    Anubhab, Ghosh
    et al.
    KTH Royal Institute of Technology.
    Fontcuberta, Aleix Espuña
    Abdalmoaty, Mohamed
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Chatterjee, Saikat
    KTH Royal Institute of Technology.
    Time-Varying Normalizing Flows for Dynamical Signals2022Conference paper (Refereed)
    Abstract [en]

    We develop a time-varying normalizing flow (TVNF) for explicit generative modeling of dynamical signals. Being explicit, it can generate samples of dynamical signals, and compute the likelihood of a (given) dynamical signal sample. In the proposed model, signal flow in the layers of the normalizing flow is a function of time, which is realized using an encoded representation that is the output of a recurrent neural network (RNN). Given a set of dynamical signals, the parameters of TVNF are learned according to a maximum-likelihood approach in conjunction with gradient descent (backpropagation). Use of the proposed model is illustrated for a toy application scenario-maximum-likelihood based speech-phone classification task.

  • 38.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Channel Estimation and Prediction for 5G Applications2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Accurate channel state information (CSI) is important for many candidate techniques of future wireless communication systems. However, acquiring CSI can sometimes be difficult, especially if the user equipment is mobile in which case the future channel realisations must be estimated/predicted. In realistic settings the predictability of radio channels is limited due to measurement noise, limited model orders and since the fading statistics must be modelled based on a set of limited and noisy training data.

    In this thesis, the limits of predictability for the radio channel are investigated. Results show that the predictability is limited primarily due to limitations in the training data, while the model order provides a second order limitation effect and the measurement noise comes in as a third order effect.

    Then, a Kalman-based linear filter is studied for potential 5G technologies:

    Coherent coordinated multipoint joint transmission, where channel predictions and the covariance matrix of the prediction error are used to design a robust linear precoder, evaluated in a three base station system. Results show that prediction improves the CSI for the pedestrian users such that system delays of 10 ms are acceptable. The use of the covariance matrix is important for difficult user groups, but of less importance with a simple user grouping system proposed.

    Massive multiple-input multiple-output (MIMO) in frequency division duplex (FDD) systems were a reduced, suboptimal, Kalman filter is suggested to estimate channels based on non-orthogonal pilots. By introducing a fixed grid of beams, the system generates sparsity in the channel vectors seen by each user, which then estimates its most relevant channels based on unique pilot codes for each beam. Results show that there is a 5 dB loss compared to orthogonal pilots.

    Downlink time division duplex (TDD) channels are estimated based on uplink pilots. By using a predictor antenna, which scouts the channel in advance, the desired downlink channel can be estimated using pilot-based estimates of the channels before and after it (in space). Results indicate that, with the help of Kalman smoothing, predictor antennas can enable accurate CSI for TDD downlinks at vehicular velocities of 80 km/h.

    List of papers
    1. Kalman predictions for multipoint OFDM downlink channels
    Open this publication in new window or tab >>Kalman predictions for multipoint OFDM downlink channels
    2014 (English)Report (Other academic)
    National Category
    Engineering and Technology
    Research subject
    Electrical Engineering with specialization in Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-235010 (URN)
    Available from: 2014-10-28 Created: 2014-10-28 Last updated: 2018-03-07
    2. Design and measurement based evaluations of coherent JT CoMP: A study of precoding, user grouping and resource allocation using predicted CSI
    Open this publication in new window or tab >>Design and measurement based evaluations of coherent JT CoMP: A study of precoding, user grouping and resource allocation using predicted CSI
    2014 (English)In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499Article in journal (Refereed) Published
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:uu:diva-235014 (URN)DOI:10.1186/1687-1499-2014-100 (DOI)
    Available from: 2014-10-28 Created: 2014-10-28 Last updated: 2018-11-08
    3. Robust linear precoder for coordinated multipoint joint transmission under limited backhaul with imperfect CSI
    Open this publication in new window or tab >>Robust linear precoder for coordinated multipoint joint transmission under limited backhaul with imperfect CSI
    2014 (English)In: 2014 11TH INTERNATIONAL SYMPOSIUM ON WIRELESS COMMUNICATIONS SYSTEMS (ISWCS), 2014, p. 138-143Conference paper, Published paper (Refereed)
    Abstract [en]

    Coordinated Multipoint (COMP) transmission provides high theoretic gains in spectral efficiency, in particular with coherent linear Joint Transmission (JT) to multiple users. However, this requires high backhaul capacity. If the backhaul requirement cannot be met by the system, then CoNIP gains decrease as the linear precoder matrix must be adjusted to include zeros. To minimize the loss of CoMP gains, all elements in the precoder should be adjusted as zeros are added to the precoder. We here propose a low complexity method for adjusting a precoder matrix when some elements are required to be zero, with respect to a robust MSE criterion. This is done by introducing penalties on specific precoder matrix elements. This generalized MSE criterion can then be used as a low complexity tool for optimizing e.g. with respect to sum-rate. Results show that this does indeed provide a better solution than if zeros are added separately. It is especially beneficial for cell edge users, i.e. for the same users that can gain the most from JT CoNIP.

    National Category
    Engineering and Technology
    Research subject
    Electrical Engineering with specialization in Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-235007 (URN)000363906500027 ()978-1-4799-5863-4 (ISBN)
    Conference
    International Symposium on Wireless Communication Systems ISWCS, Barcelona, Spanien, 25-29 Augusti
    Available from: 2014-10-28 Created: 2014-10-28 Last updated: 2018-03-07Bibliographically approved
    4. Joint reference signal design and Kalman/Wiener channel estimation for FDD massive MIMO. Extended Report Version.
    Open this publication in new window or tab >>Joint reference signal design and Kalman/Wiener channel estimation for FDD massive MIMO. Extended Report Version.
    2017 (English)Report (Other academic)
    Place, publisher, year, edition, pages
    Uppsala: Signals and Systems, Uppsala University, 2017
    Series
    Report r1701
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:uu:diva-330705 (URN)
    Available from: 2017-10-03 Created: 2017-10-03 Last updated: 2018-03-07
    5. Kalman Smoothing for Irregular Pilot Patterns: A Case Study for Predictor Antennas in TDD Systems
    Open this publication in new window or tab >>Kalman Smoothing for Irregular Pilot Patterns: A Case Study for Predictor Antennas in TDD Systems
    2018 (English)In: 2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC), IEEE, 2018Conference paper, Published paper (Refereed)
    Abstract [en]

    For future large-scale multi-antenna systems, channel orthogonal downlink pilots are not feasible due to extensive overhead requirements. Instead, channel reciprocity can be utilized in time division duplex (TDD) systems so that the downlink channel estimates can be based on pilots transmitted during the uplink. User mobility affects the reciprocity and makes the channel state information outdated for high velocities and/or long downlink subframe durations. Channel extrapolation, e.g. through Kalman prediction, can reduce the problem but is also limited by high velocities and long downlink subframes. An alternative solution has been proposed where channel predictions are made with the help of an extra antenna, e.g. on the roof of a car, so called predictor antenna, with the primary objective to measure the channel at a position that is later encountered by the rearward antenna(s). The predictor antenna is not directly limited by high velocities and allows the channel in the downlinks to be interpolated rather than extrapolated. One remaining challenge here is to obtain a good interpolation of the uplink channel estimate, since a sequence of uplink reference signals (pilots) will be interrupted by downlink subframes. We here evaluate a Kalman smoothing estimate of the downlink channels and compare it to a cubic spline interpolation. These results are also compared to results where uplink channels are estimated through Kalman filters and predictors. Results are based on measured channels and show that with Kalman smoothing, predictor antennas can enable accurate channel estimates for a longer downlink period at vehicular velocities. The gaps in the uplink pilot stream, due to downlink subframes, can have durations that correspond to a vehicle movement of up to 0.75 carrier wavelengths in space, for Rayleigh-like non-line-of-sight fading.

    Place, publisher, year, edition, pages
    IEEE, 2018
    National Category
    Telecommunications
    Identifiers
    urn:nbn:se:uu:diva-344267 (URN)10.1109/PIMRC.2018.8581030 (DOI)000457761900206 ()978-1-5386-6009-6 (ISBN)
    Conference
    29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC'18), SEP 09-12, 2018, Bologna, Italy
    Note

    Received a PIMRC2018 Best Paper Award

    Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2020-05-18Bibliographically approved
    Download full text (pdf)
    fulltext
    Download (jpg)
    presentationsbild
  • 39.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Design Aspects of Coordinated Multipoint Transmission: A Study of Channel Predictions, Resource Allocation, User Grouping and Robust Linear Precoding for Coherent Joint Transmission2014Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Shadowed areas and interference at cell borders pose great challenges for future wireless broadband systems. Coordinated Multipoint (CoMP) coherent joint transmission has shown the potential to overcome these challenges by turning harmful interference into useful signal power. However, there are obstacles to overcome before coherent joint transmission CoMP can be deployed. Some of these are the investigated in this thesis.

    First, coherent joint transmission requires very accurate Channel State Information (CSI), but unfortunately long system latencies cause outdating of the CSI. This can to some extend be counteracted by channel predictions. Two schemes are here investigated for predicting downlink Frequency Division Duplex (FDD) Orthogonal Frequency Division Multiplexing (OFDM) channels; Kalman filters and “predictor antennas”. The first is well suited for slow moving users, e.g. pedestrians or cyclists, as it does not require any special antenna setup. The second, which utilizes an extra antenna, located in front of the main receive antennas, is well suited for vehicular users, such as buses or trams, as these require long spatial prediction horizon.

    Second, a user grouping and resource allocation scheme is investigated. This scheme forms CoMP groups by local resource allocations and provides multi-user diversity gains very close to the optimal gains, found through an extensive combinatorial search. It has very low complexity, requires less feedback capacity than other schemes and places no demands on backhaul capacity.

    Finally, a linear precoder, which is robust to errors in the CSI, is investigated. This precoder takes the covariances of the channel errors into account while optimizing a Mean Squared Error (MSE) criterion. The MSE criterion includes design parameters that can be used as flexible tools for low dimensional searches with respect to an arbitrary optimization criterion, e.g. a weighted sum-rate criterion. The precoder design is also extended to handle backhaul constraints.

    Results show that with the combination of these three schemes: channel predictions, the proposed user grouping and resource allocation scheme and the robust linear precoder, then coherent joint transmission will indeed provide large capacity gains.

    List of papers
    1. Measurement-based evaluation of robust linear precoding for downlink CoMP
    Open this publication in new window or tab >>Measurement-based evaluation of robust linear precoding for downlink CoMP
    2012 (English)In: IEEE International Conference on Communications, ICC, Ottawa, Canada, 2012Conference paper, Published paper (Refereed)
    Abstract [en]

    We study the design and evaluation of joint processing coordinated multipoint (CoMP) downlink transmission. Precoders will then be designed based on outdated channel state information (CSI), so interference cannot be eliminated completely as by an ideal zero-forcing (ZF) solution. We here strive to design and evaluate realistic linear transmit schemes. Kalman predictors are used for orthogonal frequency-division multiplexing (OFDM) channels. They provide optimal linear predictions and also estimates of their uncertainty. Robust linear precoders are designed based on these uncertainty estimates. We introduce and use robust linear quadratic optimal feedforward control, with the criterion averaged (marginalized) over the CSI uncertainty. This flexible solution performs minimum mean square error (MSE) minimization. It can also iteratively optimize other criteria, such as sum-rate. The prediction- and transmission performance is evaluated using measured data on 20 MHz OFDM downlinks from three base stations, for users at fast pedestrian velocities. Downlink CoMP is here also compared to cellular transmission, that uses orthogonal resources within cells but allows uncontrolled interference between cells.

    National Category
    Signal Processing
    Research subject
    Electrical Engineering with specialization in Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-181051 (URN)
    Conference
    IEEE International Conference on Communications, ICC, June 10 - 15, Ottawa, Canada.
    Available from: 2012-09-17 Created: 2012-09-17 Last updated: 2014-06-04Bibliographically approved
    2. Design and measurement based evaluations of coherent JT CoMP: a study of precoding, user grouping and resource allocation using predicted CSI
    Open this publication in new window or tab >>Design and measurement based evaluations of coherent JT CoMP: a study of precoding, user grouping and resource allocation using predicted CSI
    2014 (English)In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, p. 100-Article in journal (Refereed) Published
    Abstract [en]

    Coordinated multipoint (CoMP) transmission provides high theoretic gains in spectral efficiency with coherent joint transmission (JT) to multiple users. However, this requires accurate channel state information at the transmitter (CSIT) and also user groups with spatially compatible users. The aim of this paper is to use measured channels to investigate if significant CoMP gains can still be obtained with channel estimation errors. This turns out to be the case, but requires the combination of several techniques. We here focus on coherent downlink JT CoMP to multiple users within a cluster of cooperating base stations. The use of Kalman predictors is investigated to estimate the complex channel gains at the moment of transmission. It is shown that this can provide sufficient CSIT quality for JT CoMP even for long (> 20 ms) system delays at 2.66 GHz at pedestrian velocities or, for lower delays, at 500 MHz, at vehicular velocities. A user grouping and resource allocation scheme that provides appropriate groups for CoMP is also suggested. It provides performance close to that obtained by exhaustive search at very low complexity, low feedback cost and very low backhaul cost. Finally, a robust linear precoder that takes channel uncertainties into account when designing the precoding matrix is considered. We show that, in challenging scenarios, this provides large gains compared with zero-forcing precoding. Evaluations of these design elements are based on measured channels with realistic noise and intercluster interference assumptions. These show that high JT CoMP gains can be expected, on average over large sets of user positions, when the above techniques are combined - especially in severely intracluster interference limited scenarios.

    Keywords
    Coordinated Multipoint, channel predictions, user grouping, resource allocation, robust precoding
    National Category
    Signal Processing
    Research subject
    Electrical Engineering with specialization in Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-224254 (URN)10.1186/1687-1499-2014-100 (DOI)000347399300001 ()
    Available from: 2014-05-07 Created: 2014-05-07 Last updated: 2018-11-08Bibliographically approved
    3. Robust Linear Precoder for Coordinated Multipoint Joint Transmission under Limited Backhaul with Imperfect CSI
    Open this publication in new window or tab >>Robust Linear Precoder for Coordinated Multipoint Joint Transmission under Limited Backhaul with Imperfect CSI
    (English)Manuscript (preprint) (Other academic)
    National Category
    Engineering and Technology
    Research subject
    Electrical Engineering with specialization in Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-224255 (URN)
    Available from: 2014-05-07 Created: 2014-05-07 Last updated: 2014-06-04
    4. Analysis and Measurement of Multiple Antenna Systems for Fading Channel Prediction in Moving Relays
    Open this publication in new window or tab >>Analysis and Measurement of Multiple Antenna Systems for Fading Channel Prediction in Moving Relays
    Show others...
    2014 (English)In: 2014 8TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 2014, p. 2015-2019Conference paper, Published paper (Other academic)
    Abstract [en]

    The performance of wireless data transmission to mobile vehicles is improved if channel state information is available at the transmitter but movement of vehicles causes outdating of channel estimates. The concept of a predictor antenna has recently been proposed, where an antenna is placed in front of other antennas on the roof of the vehicle to sense the radio environment in advance. This can comparatively provide an order-of-magnitude improvement in channel prediction performance. A potential problem with this idea is that closely placed antennas will experience mutual electromagnetic couplings. These may reduce the efficiency of the predictor antenna concept if they are not taken into account. In this paper, we discuss about how to treat the forgoing issue and eventually evaluate a promising candidate on measured channels. We argue that only open-circuit voltage method would be realistic for the present application. The usefulness of the proposed decoupling method is demonstrated on field measurements obtained in downtown Dresden, Germany. We also partly address the sensitivity of the open-circuit decoupling method to the accuracy of the utilized network parameters.

    Series
    Proceedings of the European Conference on Antennas and Propagation, ISSN 2164-3342
    Keywords
    Multi-element antennas; channel state prediction; moving relays; multipath measurement
    National Category
    Engineering and Technology
    Research subject
    Electrical Engineering with specialization in Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-224256 (URN)978-88-907018-4-9 (ISBN)
    Conference
    The 8th European Conference on Antennas and Propagation (EuCAP), to be held at the World Forum in The Hague, The Netherlands, on 6-11 April 2014.
    Note

    This paper has been presented as a poster on: the 8th European Conference on Antennas and Propagation (EuCAP), in The Hague, The Netherlands, on 6-11 April 2014, and will appear in the proceedings

    Available from: 2014-05-08 Created: 2014-05-07 Last updated: 2015-11-06Bibliographically approved
    5. Kalman Predictions for Multipoint OFDM Downlink Channels
    Open this publication in new window or tab >>Kalman Predictions for Multipoint OFDM Downlink Channels
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Coordinated Multipoint (CoMP) transmission provides high theoreticgains in spectral eciency with coherent Joint Transmission (JT) to mul-tiple users. However, this requires accurate Channel State Information atthe Transmitter (CSIT). Unfortunately, coherent JT CoMP often is accom-panied by long system delays, due to e.g. data sharing over backhaul links.Therefore, the CSIT will be outdated.This report provides a detailed description on how to increase the accu-racy of the CSIT by utilizing Kalman lters to predict Orthogonal FrequencyDivision Multiplexing (OFDM) downlink channels. The small scale fading ofthese channels are modeled by Auto Regressive (AR) models of nite order.The report includes descriptions on how to estimate these models basedon past knowledge of the channel as well as analytical result on the pre-dictability of such models. Dierent technical design aspects for deployingthe Kalman lters in communication, such as pilot patterns, AR model esti-mations and the location of Kalman lters that predict downlink FrequencyDivision Duplex (FDD) channels, are also discussed.The aim of the report is to in detail describe the prediction procedureused in previous work. Some of the results from this previous work arehere presented and extended to provide a complete overview. All simulationresults are based on measured channels.The report also includes a description on how to model block-fading chan-nels with a specied channel accuracy that would have been obtained withKalman predictions. This model can then be used for system simulations.V:

    Keywords
    Linear predictions of OFDM channels, outdated channel state information (CSI), Coordinated Multipoint (CoMP), Predictability of radio channles, AR modelling of radio channels
    National Category
    Engineering and Technology
    Research subject
    Electrical Engineering with specialization in Signal Processing
    Identifiers
    urn:nbn:se:uu:diva-224263 (URN)
    Available from: 2014-05-08 Created: 2014-05-08 Last updated: 2014-06-04
  • 40.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Design and measurement based evaluations of coherent JT CoMP: a study of precoding, user grouping and resource allocation using predicted CSI2014In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, p. 100-Article in journal (Refereed)
    Abstract [en]

    Coordinated multipoint (CoMP) transmission provides high theoretic gains in spectral efficiency with coherent joint transmission (JT) to multiple users. However, this requires accurate channel state information at the transmitter (CSIT) and also user groups with spatially compatible users. The aim of this paper is to use measured channels to investigate if significant CoMP gains can still be obtained with channel estimation errors. This turns out to be the case, but requires the combination of several techniques. We here focus on coherent downlink JT CoMP to multiple users within a cluster of cooperating base stations. The use of Kalman predictors is investigated to estimate the complex channel gains at the moment of transmission. It is shown that this can provide sufficient CSIT quality for JT CoMP even for long (> 20 ms) system delays at 2.66 GHz at pedestrian velocities or, for lower delays, at 500 MHz, at vehicular velocities. A user grouping and resource allocation scheme that provides appropriate groups for CoMP is also suggested. It provides performance close to that obtained by exhaustive search at very low complexity, low feedback cost and very low backhaul cost. Finally, a robust linear precoder that takes channel uncertainties into account when designing the precoding matrix is considered. We show that, in challenging scenarios, this provides large gains compared with zero-forcing precoding. Evaluations of these design elements are based on measured channels with realistic noise and intercluster interference assumptions. These show that high JT CoMP gains can be expected, on average over large sets of user positions, when the above techniques are combined - especially in severely intracluster interference limited scenarios.

    Download full text (pdf)
    fulltext
  • 41.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Aronsson, Daniel
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Measurement-based evaluation of robust linear precoding for downlink CoMP2012In: IEEE International Conference on Communications, ICC, Ottawa, Canada, 2012Conference paper (Refereed)
    Abstract [en]

    We study the design and evaluation of joint processing coordinated multipoint (CoMP) downlink transmission. Precoders will then be designed based on outdated channel state information (CSI), so interference cannot be eliminated completely as by an ideal zero-forcing (ZF) solution. We here strive to design and evaluate realistic linear transmit schemes. Kalman predictors are used for orthogonal frequency-division multiplexing (OFDM) channels. They provide optimal linear predictions and also estimates of their uncertainty. Robust linear precoders are designed based on these uncertainty estimates. We introduce and use robust linear quadratic optimal feedforward control, with the criterion averaged (marginalized) over the CSI uncertainty. This flexible solution performs minimum mean square error (MSE) minimization. It can also iteratively optimize other criteria, such as sum-rate. The prediction- and transmission performance is evaluated using measured data on 20 MHz OFDM downlinks from three base stations, for users at fast pedestrian velocities. Downlink CoMP is here also compared to cellular transmission, that uses orthogonal resources within cells but allows uncontrolled interference between cells.

    Download full text (pdf)
    fulltext
  • 42.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Zirwas, Wolfgang
    Nokia Bell Labs, D-81541 Munich, Germany.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Low-Overhead Cyclic Reference Signals for Channel Estimation in FDD Massive MIMO2019In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 5, p. 3279-3291Article in journal (Refereed)
    Abstract [en]

    Massive multiple input multiple output (MIMO) transmission and coordinated multipoint transmission are candidate technologies for increasing data throughput in evolving 5G standards. Frequency division duplex (FDD) is likely to remain predominant in large parts of the spectrum below 6 GHz for future 5G systems. Therefore, it is important to estimate the downlink FDD channels from a very large number of antennas, while avoiding an excessive downlink reference signal overhead. We here propose and investigate a three part solution. First, massive MIMO downlinks use a fixed grid of beams. For each user, only a subset of beams will then be relevant, and require estimation. Second, sets of coded reference signal sequences, with cyclic patterns over time, are used. Third, each terminal estimates its most relevant channels. We here propose and compare a linear mean square estimation and a Kalman estimation. Both utilize frequency and antenna correlation, and the later also utilizes temporal correlation. In extensive simulations, this scheme provides channel estimates that lead to an insignificant beamforming performance degradation as compared to full channel knowledge. The cyclic pattern of coded reference signals is found to be important for reliable channel estimation, without having to adjust the reference signals to specific users.

  • 43.
    Aronsson, Daniel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Svensson, Tommy
    Chalmers University of Technology, Dept of Signals and Systems.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Performance evaluation of memory-less and Kalman-based channel estimation for OFDMA2009In: IEEE Vehicular Technology Conference, Barcelona, Spanien, April 26-29, 2009, 2009, p. 2314-2318Conference paper (Refereed)
    Abstract [en]

    The next generation wireless systems based on Orthogonal Frequency Division Multiple Access (OFDMA) need to operate in widely different deployment and usage scenarios. Thus, support for flexible resource allocation is important. In this paper we investigate the performance or different memory-less and memory-based channel estimators for different OFDMA subcarrier allocation schemes and different pilot patterns. We evaluate the performance in various fading environments and for different user terminal velocities. The results show that channel estimation can perform well enough for time-frequency localized resources as small as 22 channel symbols with two pilots in many important scenarios. The results provided can be used to identify appropriate subcarrier allocations for the next generation OFDMA based wireless systems.

  • 44.
    Asan, Noor Badariah
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
    Velander, Jacob
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
    Redzwan, Syaiful
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
    Perez, Mauricio D.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
    Hassan, Emadeldeen
    Umeå University, Department of Computing Science, Umeå, Sweden.
    Blokhuis, Taco J.
    Maastricht University Medical Center, Department of Surgery, Maastricht, The Netherland.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Augustine, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
    Effect of thickness inhomogeneity in fat tissue on in-body microwave propagation2018In: 2018 IEEE International Microwave Biomedical Conference (IMBioC), Philadelphia, USA: IEEE, 2018, p. 136-138Conference paper (Refereed)
    Abstract [en]

    In recent studies, it has been found that fat tissue can be used as a microwave communication channel. In this article, the effect of thickness inhomogeneities in fat tissues on the performance of in-body microwave communication at 2.45 GHz is investigated using phantom models. We considered two models namely concave and convex geometrical fat distribution to account for the thickness inhomogeneities. The thickness of the fat tissue is varied from 5 mm to 45 mm and the Gap between the transmitter/receiver and the starting and ending of concavity/convexity is varied from 0 mm to 25 mm for a length of 100 mm to study the behavior in the microwave propagation. The phantoms of different geometries, concave and convex, are used in this work to validate the numerical studies. It was noticed that the convex model exhibited higher signal coupling by an amount of 1 dB (simulation) and 2 dB (measurement) compared to the concave model. From the study, it was observed that the signal transmission improves up to 30 mm thick fat and reaches a plateau when the thickness is increased further.

    Download full text (pdf)
    fulltext
  • 45.
    Asplund, Teo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Precise Image-Based Measurements through Irregular Sampling2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Mathematical morphology is a theory that is applicable broadly in signal processing, but in this thesis we focus mainly on image data. Fundamental concepts of morphology include the structuring element and the four operators: dilation, erosion, closing, and opening. One way of thinking about the role of the structuring element is as a probe, which traverses the signal (e.g. the image) systematically and inspects how well it "fits" in a certain sense that depends on the operator.

    Although morphology is defined in the discrete as well as in the continuous domain, often only the discrete case is considered in practice. However, commonly digital images are a representation of continuous reality and thus it is of interest to maintain a correspondence between mathematical morphology operating in the discrete and in the continuous domain. Therefore, much of this thesis investigates how to better approximate continuous morphology in the discrete domain. We present a number of issues relating to this goal when applying morphology in the regular, discrete case, and show that allowing for irregularly sampled signals can improve this approximation, since moving to irregularly sampled signals frees us from constraints (namely those imposed by the sampling lattice) that harm the correspondence in the regular case. The thesis develops a framework for applying morphology in the irregular case, using a wide range of structuring elements, including non-flat structuring elements (or structuring functions) and adaptive morphology. This proposed framework is then shown to better approximate continuous morphology than its regular, discrete counterpart.

    Additionally, the thesis contains work dealing with regularly sampled images using regular, discrete morphology and weighting to improve results. However, these cases can be interpreted as specific instances of irregularly sampled signals, thus naturally connecting them to the overarching theme of irregular sampling, precise measurements, and mathematical morphology.

    List of papers
    1. Mathematical morphology on irregularly sampled data in one dimension
    Open this publication in new window or tab >>Mathematical morphology on irregularly sampled data in one dimension
    2017 (English)In: Mathematical Morphology - Theory and Applications, ISSN 2353-3390, Vol. 2, no 1, p. 1-24Article in journal (Refereed) Published
    National Category
    Computer Sciences
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-337288 (URN)10.1515/mathm-2017-0001 (DOI)
    Funder
    Swedish Research Council, 2014-5983
    Available from: 2017-12-29 Created: 2017-12-21 Last updated: 2019-10-17Bibliographically approved
    2. Mathematical Morphology on Irregularly Sampled Signals
    Open this publication in new window or tab >>Mathematical Morphology on Irregularly Sampled Signals
    2017 (English)In: Computer Vision – ACCV 2016 Workshops. ACCV 2016, Springer, 2017, Vol. 10117, p. 506-520Conference paper, Published paper (Refereed)
    Abstract [en]

    This paper introduces a new operator that can be used to approximate continuous-domain mathematical morphology on irregularly sampled surfaces. We define a new way of approximating the continuous domain dilation by duplicating and shifting samples according to a flat continuous structuring element. We show that the proposed algorithm can better approximate continuous dilation, and that dilations may be sampled irregularly to achieve a smaller sampling without greatly compromising the accuracy of the result.

    Place, publisher, year, edition, pages
    Springer, 2017
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10117
    National Category
    Computer Sciences Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-309921 (URN)10.1007/978-3-319-54427-4_37 (DOI)000426193700037 ()978-3-319-54427-4 (ISBN)978-3-319-54426-7 (ISBN)
    Conference
    13th Asian Conference on Computer Vision (ACCV), Taipei, Taiwan, November 20-24, 2016
    Funder
    Swedish Research Council, 2014-5983
    Available from: 2016-12-08 Created: 2016-12-08 Last updated: 2019-10-17Bibliographically approved
    3. Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes
    Open this publication in new window or tab >>Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes
    Show others...
    2019 (English)In: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, Springer Nature , 2019Conference paper, Published paper (Refereed)
    Abstract [en]

    This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene.

    Place, publisher, year, edition, pages
    Springer Nature, 2019
    Series
    Lecture Notes In Computer Science, ISSN 0302-9743, E-ISSN 1611-3349
    National Category
    Signal Processing
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-388524 (URN)10.1007/978-3-030-20867-7_29 (DOI)000558276600029 ()978-3-030-20866-0 (ISBN)978-3-030-20867-7 (ISBN)
    Conference
    14th International Symposium on Mathematical Morphology (ISMM 2019), 8-10 July, 2019, Saarbrücken, Germany
    Funder
    Swedish Research Council, 2014-5983
    Available from: 2019-07-01 Created: 2019-07-01 Last updated: 2020-10-06Bibliographically approved
    4. Adaptive Mathematical Morphology on Irregularly Sampled Signals in Two Dimensions
    Open this publication in new window or tab >>Adaptive Mathematical Morphology on Irregularly Sampled Signals in Two Dimensions
    2020 (English)In: Mathematical Morphology - Theory and Applications, ISSN 2353-3390, Vol. 4, no 1, p. 108-126Article in journal (Refereed) Published
    Abstract [en]

    This paper proposes a way of better approximating continuous, two-dimensional morphology in the discrete domain, by allowing for irregularly sampled input and output signals. We generalize previous work to allow for a greater variety of structuring elements, both flat and non-flat. Experimentally we show improved results over regular, discrete morphology with respect to the approximation of continuous morphology. It is also worth noting that the number of output samples can often be reduced without sacrificing the quality of the approximation, since the morphological operators usually generate output signals with many plateaus, which, intuitively do not need a large number of samples to be correctly represented. Finally, the paper presents some results showing adaptive morphology on irregularly sampled signals.

    Place, publisher, year, edition, pages
    Walter de Gruyter, 2020
    National Category
    Signal Processing
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-395204 (URN)10.1515/mathm-2020-0104 (DOI)
    Funder
    Swedish Research Council, 2014-5983
    Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2023-11-29Bibliographically approved
    5. Estimating the Gradient for Images with Missing Samples Using Elliptical Structuring Elements
    Open this publication in new window or tab >>Estimating the Gradient for Images with Missing Samples Using Elliptical Structuring Elements
    (English)In: Article in journal (Refereed) Submitted
    National Category
    Signal Processing
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-395200 (URN)
    Funder
    Swedish Research Council, 2014-5983
    Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2019-10-25
    6. A Faster, Unbiased Path Opening by Upper Skeletonization and Weighted Adjacency Graphs
    Open this publication in new window or tab >>A Faster, Unbiased Path Opening by Upper Skeletonization and Weighted Adjacency Graphs
    2016 (English)In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 25, no 12, p. 5589-5600Article in journal (Refereed) Published
    Abstract [en]

    The path opening is a filter that preserves bright regions in the image in which a path of a certain length L fits. A path is a (not necessarily straight) line defined by a specific adjacency relation. The most efficient implementation known scales as O(min(L, d, Q)N) with the length of the path, L, the maximum possible path length, d, the number of graylevels, Q, and the image size, N. An approximation exists (parsimonious path opening) that has an execution time independent of path length. This is achieved by preselecting paths, and applying 1D openings along these paths. However, the preselected paths can miss important structures, as described by its authors. Here, we propose a different approximation, in which we preselect paths using a grayvalue skeleton. The skeleton follows all ridges in the image, meaning that no important line structures will be missed. An H-minima transform simplifies the image to reduce the number of branches in the skeleton. A graph-based version of the traditional path opening operates only on the pixels in the skeleton, yielding speedups up to one order of magnitude, depending on image size and filter parameters. The edges of the graph are weighted in order to minimize bias. Experiments show that the proposed algorithm scales linearly with image size, and that it is often slightly faster for longer paths than for shorter paths. The algorithm also yields the most accurate results- as compared with a number of path opening variants-when measuring length distributions.

    Keywords
    graph theory, image filtering, transforms, 1D openings, H-minima transform, filter parameters, graph edges, grayvalue skeleton, image analysis, image filtering, image size, unbiased path opening, upper skeletonization, weighted adjacency graphs, Approximation algorithms, Gray-scale, Image edge detection, Length measurement, Periodic structures, Skeleton, Transforms, Path opening, granulometry, image analysis, length distribution, line segment, mathematical morphology, unbiased
    National Category
    Other Computer and Information Science
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-309087 (URN)10.1109/TIP.2016.2609805 (DOI)000388205100007 ()
    Funder
    Swedish Research Council, 2014-5983
    Available from: 2016-12-02 Created: 2016-12-02 Last updated: 2019-10-17Bibliographically approved
    Download full text (pdf)
    fulltext
    Download (jpg)
    presentationsbild
  • 46.
    Asplund, Teo
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Luengo Hendriks, Cris L.
    Flagship Biosciences Inc, Colorado, USA..
    Thurley, Matthew J.
    Luleå tekniska universitet.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Adaptive Mathematical Morphology on Irregularly Sampled Signals in Two Dimensions2020In: Mathematical Morphology - Theory and Applications, ISSN 2353-3390, Vol. 4, no 1, p. 108-126Article in journal (Refereed)
    Abstract [en]

    This paper proposes a way of better approximating continuous, two-dimensional morphology in the discrete domain, by allowing for irregularly sampled input and output signals. We generalize previous work to allow for a greater variety of structuring elements, both flat and non-flat. Experimentally we show improved results over regular, discrete morphology with respect to the approximation of continuous morphology. It is also worth noting that the number of output samples can often be reduced without sacrificing the quality of the approximation, since the morphological operators usually generate output signals with many plateaus, which, intuitively do not need a large number of samples to be correctly represented. Finally, the paper presents some results showing adaptive morphology on irregularly sampled signals.

    Download full text (pdf)
    fulltext
  • 47.
    Asplund, Teo
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Luengo Hendriks, Cris L.
    Flagship Biosciences Inc, Colorado, USA..
    Thurley, Matthew J.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Estimating the Gradient for Images with Missing Samples Using Elliptical Structuring ElementsIn: Article in journal (Refereed)
  • 48.
    Asplund, Teo
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Serna, Andrés
    Terra3D.
    Marcotegui, Beatriz
    MINES ParisTech, PSL Research University, CMM - Centre for Mathematical Morphology.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Luengo Hendriks, Cris L.
    Flagship Biosciences Inc..
    Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes2019In: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, Springer Nature , 2019Conference paper (Refereed)
    Abstract [en]

    This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene.

  • 49.
    Asraf, Daniel
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Optimal Detectors for Transient Signal Families and Nonlinear Sensors: Derivations and Applications2003Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis is concerned with detection of transient signal families and detectors in nonlinear static sensor systems. The detection problems are treated within the framework of likelihood ratio based binary hypothesis testing.

    An analytical solution to the noncoherent detection problem is derived, which in contrast to the classical noncoherent detector, is optimal for wideband signals. An optimal detector for multiple transient signals with unknown arrival times is also derived and shown to yield higher detection performance compared to the classical approach based on the generalized likelihood ratio test.

    An application that is treated in some detail is that of ultrasonic nondestructive testing, particularly pulse-echo detection of defects in elastic solids. The defect detection problem is cast as a composite hypothesis test and a methodology, based on physical models, for designing statistically optimal detectors for cracks in elastic solids is presented. Detectors for defects with low computational complexity are also formulated based on a simple phenomenological model of the defect echoes. The performance of these detectors are compared with the physical model-based optimal detector and is shown to yield moderate performance degradation.

    Various aspects of optimal detection in static nonlinear sensor systems are also treated, in particular the stochastic resonance (SR) phenomenon which, in this context, implies noise enhanced detectability. Traditionally, SR has been quantified by means of the signal-to-noise ratio (SNR) and interpreted as an increase of a system's information processing capability. Instead of the SNR, rigorous information theoretic distance measures, which truly can support the claim of noise enhanced information processing capability, are proposed as quantifiers for SR. Optimal detectors are formulated for two static nonlinear sensor systems and shown to exhibit noise enhanced detectability.

    List of papers
    1. An analytical series expansion solution to the problem of noncoherent detection
    Open this publication in new window or tab >>An analytical series expansion solution to the problem of noncoherent detection
    2004 (English)In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 50, no 12, p. 3369-3375Article in journal (Refereed) Published
    Abstract [en]

    The well-known noncoherent detection problem concerns optimal detection of an amplitude-modulated sinusoid, with an unknown phase angle, corrupted by additive Gaussian noise. The classical solution to this problem is the noncoherent detector which is known to be optimal if the envelope belongs to a specific set of functions or satisfies the narrow-band approximation i.e., that the bandwidth of the envelope is narrow in comparison with the (carrier) frequency of the sinusoid. In this work, an analytical series expansion solution to the likelihood ratio for the noncoherent detection problem is derived. This solution offers a generalization of the noncoherent detector in which the conditions imposed on the envelope stated above have been relaxed. Analytical expressions for the joint probability density functions (pdfs) of the in-phase and quadrature components, jointly expressed in polar coordinates, are also derived under the signal-plus-noise and the noise-only hypotheses, respectively. Numerical simulations of the detector performance are presented in the form of receiver operating characteristics (ROC) and minimum probability of error curves. The results from a comparison of the general analytical solution with the classical noncoherent detector show significant differences between the two detectors when the narrow-band approximation does not hold.

    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:uu:diva-90173 (URN)10.1109/TIT.2004.838396 (DOI)
    Available from: 2003-03-17 Created: 2003-03-17 Last updated: 2017-12-14Bibliographically approved
    2. Detection of Multiple Transient Signals with Unknown Arrival Times
    Open this publication in new window or tab >>Detection of Multiple Transient Signals with Unknown Arrival Times
    2005 (English)In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 51, no 5, p. 1856-1860Article in journal (Refereed) Published
    Abstract [en]

    The problem of optimal detection of signal transients with unknown arrival times contaminated by additive Gaussian noise is considered. The transients are assumed to be time continuous and belong to a parameterized family with the uncertainty about the parameters described by means of an a priori distribution. Under the assumption of a negligible probability that the independent transient observations overlap in time, a likelihood ratio is derived for the problem of detecting an unknown number of transients from the family, each transient with unknown arrival time. The uncertainty about the arrival times is assumed to be equal for all transients and is also described by means of a distribution. Numerical simulations of the performance of detecting a particular transient signal family are presented in the form of receiver operating characteristics (ROCs) for both the optimal detector and the classical generalized likelihood ratio test (GLRT). The results show that the optimal detector yields noticeable performance improvements over the GLRT. Moreover, the results show that the optimal detector may still outperform the GLRT when the true and modeled uncertainties about arrival times no longer agree.

    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:uu:diva-90174 (URN)10.1109/TIT.2005.846445 (DOI)
    Available from: 2003-03-17 Created: 2003-03-17 Last updated: 2017-12-14Bibliographically approved
    3. Optimal Detection of Crack Echo Families in Elastic Solids
    Open this publication in new window or tab >>Optimal Detection of Crack Echo Families in Elastic Solids
    2003 (English)In: The Journal of the Acoustical Society of America, Vol. 113, no 5, p. 2732-2741Article in journal (Refereed) Published
    Abstract [en]

    Optimal detection of a striplike crack residing in an isotropic elastic solid with coarse microstructure by means of ultrasonic nondestructive evaluation (NDE) is considered. A physics-based approach to derive an optimal detector, which achieves the theoretical limitations constrained by the underlying physics, is presented. State-of-the-art physical models of crack echoes and of stochastic backscattering from the material structure in elastic solids are introduced and unified with the theory of optimal detection to yield a practically useful nonlinear filter bank implementation of the optimal detector. Monte Carlo simulations of the detection performance for the special case of a striplike crack with uncertain angular orientation are presented in the form of receiver operating characteristics (ROCs). These new results represent the physical limitations for detecting a crack under the stated conditions and serve as performance bounds to which other detectors should be compared. A physics-based generalized likelihood ratio (GLR) detector, which relies on the same nonlinear filter bank as the optimal detector, is also presented for the special case of a striplike crack. A comparison between the optimal and the GLR detectors shows that the GLR detector only slightly reduces the performance.

    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:uu:diva-90175 (URN)12765391 (PubMedID)
    Available from: 2003-03-17 Created: 2003-03-17 Last updated: 2013-06-14Bibliographically approved
    4. Phenomenological detectors for crack echo families in elastic solids
    Open this publication in new window or tab >>Phenomenological detectors for crack echo families in elastic solids
    2004 (English)In: Journal of the Acoustical Society of America, ISSN 0001-4966, E-ISSN 1520-8524, Vol. 116, no 1, p. 379-388Article in journal (Refereed) Published
    Abstract [en]

    The potential performance of low-complexity phenomenological detectors for crack echo families in elastic solids is evaluated. Ultrasonic echoes from a strip-like crack residing in an isotropic elastic solid with coarse microstructure are considered and the achieved detector performance is compared to the theoretical upper bounds (constrained only by the underlying physics) obtained by means of a recently presented physics-based optimal detector. A phenomenological signal model for the scattering process is formulated based on the time-domain impulse-response method and used to derive detectors of low numerical complexity which are dependent on a small number of parameters. The proposed detectors are compared in terms of receiver operating characteristic curves, which are computed by means of Monte Carlo simulations for the case of a strip-like crack with uncertain angular orientation. The minimum probability of error criterion is used to optimize the detector parameters for the simulation study and shown to be useful even for small training data sets. These results show that the proposed detectors have close to optimal performance in particular for the case of high signal-to-noise ratios.

    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:uu:diva-90176 (URN)
    Available from: 2003-03-17 Created: 2003-03-17 Last updated: 2017-12-14Bibliographically approved
    5. Information-Theoretic Distance Measures and a Generalization of Stochastic Resonance
    Open this publication in new window or tab >>Information-Theoretic Distance Measures and a Generalization of Stochastic Resonance
    1998 In: Physical Review Letters, Vol. 81, no 14, p. 2850-2853Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-90177 (URN)
    Available from: 2003-03-17 Created: 2003-03-17Bibliographically approved
    6. Information-Theoretic Characterization of System Performance for a Nonlinear Magneto-Resistive Sensor
    Open this publication in new window or tab >>Information-Theoretic Characterization of System Performance for a Nonlinear Magneto-Resistive Sensor
    Show others...
    2000 In: Stochastic and Chaotic Dynamics in the Lakes, AIP Conference Proceedings 502, 2000, p. 603-608Chapter in book (Other academic) Published
    Identifiers
    urn:nbn:se:uu:diva-90178 (URN)1-56396-915-7 (ISBN)
    Available from: 2003-03-17 Created: 2003-03-17Bibliographically approved
    Download full text (pdf)
    FULLTEXT01
  • 50.
    Aubry, Augusto
    et al.
    CNR, IREA.
    De Maio, Antonio
    Universit`a degli Studi di Napoli “Federico II”.
    Piezzo, Marco
    Universit`a degli Studi di Napoli “Federico II”.
    Naghsh, Mohammad Mahdi
    Isfahan University of Technology.
    Soltanalian, Mojtaba
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Stoica, Peter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Cognitive Radar Waveform Design for Spectral Coexistence in Signal-Dependent Interference2014Conference paper (Refereed)
1234567 1 - 50 of 828
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf