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An overview of important practical aspects of continuous-time ARMA system identification
Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. AUTOMATIC CONTROL.
2006 (English)In: Circuits, Systems and Signal Processing, Vol. 25, no 1, 17-46 p.Article in journal (Refereed) Published
Abstract [en]

The problem of estimating the parameters in continuous-time autoregressive moving average (ARMA) processes from discrete-time data is considered. Both direct and indirect methods are studied, and similarities and differences are discussed. A general discussion of the inherent difficulties of the problem is given together with a comprehensive study on how the choice of the sampling interval influences the estimation result. A special focus is given to how the Cramer-Rao lower bound depends on the sampling interval.

Place, publisher, year, edition, pages
2006. Vol. 25, no 1, 17-46 p.
Identifiers
URN: urn:nbn:se:uu:diva-18095OAI: oai:DiVA.org:uu-18095DiVA: diva2:45866
Available from: 2007-02-08 Created: 2007-02-08 Last updated: 2011-01-11

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http://www.springerlink.com/content/h6t1767k7763/?p=3760524ef5084225823ef3b62d2972ad&pi=4

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Söderström, Torsten

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