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Rigorous parameter reconstruction for differential equations with noisy data
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
Univ Bergen, Dept Math, N-5008 Bergen, Norway.
2008 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 44, no 9, 2422-2426 p.Article in journal (Refereed) Published
Abstract [en]

We present a method that–given a data set, a finitely parametrized system of ordinary differential equations (ODEs), and a search space of parameters–discards portions of the search space that are inconsistent with the model ODE and data. The method is completely rigorous as it is based on validated integration of the vector field. As a consequence, no consistent parameters can be lost during the pruning phase. For data sets with moderate levels of noise, this yields a good reconstruction of the underlying parameters. Several examples are included to illustrate the merits of the method.

Place, publisher, year, edition, pages
2008. Vol. 44, no 9, 2422-2426 p.
Keyword [en]
Primary: 65G20, 34A60, Secondary: 65L09, rigorous numerics, parameter estimation, ordinary differential equations, interval analysis
National Category
Mathematics
Research subject
Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-103149DOI: 10.1016/j.automatica.2008.01.032ISI: 000259740200029OAI: oai:DiVA.org:uu-103149DiVA: diva2:217589
Available from: 2009-05-14 Created: 2009-05-14 Last updated: 2017-12-13Bibliographically approved
In thesis
1. Computer-aided Computation of Abelian integrals and Robust Normal Forms
Open this publication in new window or tab >>Computer-aided Computation of Abelian integrals and Robust Normal Forms
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This PhD thesis consists of a summary and seven papers, where various applications of auto-validated computations are studied.

In the first paper we describe a rigorous method to determine unknown parameters in a system of ordinary differential equations from measured data with known bounds on the noise of the measurements.

Papers II, III, IV, and V are concerned with Abelian integrals. In Paper II, we construct an auto-validated algorithm to compute Abelian integrals. In Paper III we investigate, via an example, how one can use this algorithm to determine the possible configurations of limit cycles that can bifurcate from a given Hamiltonian vector field. In Paper IV we construct an example of a perturbation of degree five of a Hamiltonian vector field of degree five, with 27 limit cycles, and in Paper V we construct an example of a perturbation of degree seven of a Hamiltonian vector field of degree seven, with 53 limit cycles. These are new lower bounds for the maximum number of limit cycles that can bifurcate from a Hamiltonian vector field for those degrees.

In Papers VI, and VII, we study a certain kind of normal form for real hyperbolic saddles, which is numerically robust. In Paper VI we describe an algorithm how to automatically compute these normal forms in the planar case. In Paper VII we use the properties of the normal form to compute local invariant manifolds in a neighbourhood of the saddle.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2009. vi+24 p.
Series
Uppsala Dissertations in Mathematics, ISSN 1401-2049 ; 66
Keyword
Ordinary differential equations, parameter estimation, planar Hamiltonian systems, bifurcation theory, Abelian integrals, limit cycles, normal forms, hyperbolic fixed points, numerical integration, invariant manifolds, interval analysis. 2000 Mathematics Subject Classification. 34A60, 34C07, 34C20, 37D10, 37G15, 37M20, 37M99, 65G20, 65L09, 65L70.
National Category
Mathematics
Research subject
Mathematics
Identifiers
urn:nbn:se:uu:diva-107519 (URN)978-91-506-2093-1 (ISBN)
Public defence
2009-10-09, Polhemsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2009-09-17 Created: 2009-08-14 Last updated: 2009-09-21
2. On some computer-aided proofs in analysis
Open this publication in new window or tab >>On some computer-aided proofs in analysis
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Uppsala: Department of Mathematics, Uppsala University, 2007. 14 p.
Series
U.U.D.M. report / Uppsala University, Department of Mathematics, ISSN 1101-3591 ; 2007:29
National Category
Mathematics
Research subject
Mathematics; Mathematics
Identifiers
urn:nbn:se:uu:diva-141509 (URN)
Opponent
Supervisors
Available from: 2011-01-12 Created: 2011-01-12 Last updated: 2011-01-12Bibliographically approved

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