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On-line almost-sure parameter estimation for partially observed discrete-time linear systems with known noise characteristics

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dc.contributor.authorElliott, R.
dc.contributor.authorFord, J.
dc.contributor.authorMoore, J.
dc.date.issued2002
dc.descriptionThe definitive version may be found at www.wiley.com
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>In this paper we discuss parameter estimators for fully and partially observed discrete‐time linear stochastic systems (in state‐space form) with known noise characteristics. We propose finite‐dimensional parameter estimators that are based on estimates of summed functions of the state, rather than of the states themselves. We limit our investigation to estimation of the state transition matrix and the observation matrix. We establish almost‐sure convergence results for our proposed parameter estimators using standard martingale convergence results, the Kronecker lemma and an ordinary differential equation approach. We also provide simulation studies which illustrate the performance of these estimators. Copyright © 2002 John Wiley &amp; Sons, Ltd.</jats:p>
dc.description.statementofresponsibilityRobert J. Elliott, Jason J. Ford, John B. Moore
dc.identifier.citationInternational Journal of Adaptive Control and Signal Processing, 2002; 16(6):435-453
dc.identifier.doi10.1002/acs.703
dc.identifier.issn0890-6327
dc.identifier.issn1099-1115
dc.identifier.urihttp://hdl.handle.net/2440/453
dc.language.isoen
dc.publisherJohn Wiley & Sons Ltd
dc.source.urihttp://www3.interscience.wiley.com/cgi-bin/abstract/91013642/ABSTRACT
dc.subjectadaptive estimation
dc.subjectparameter estimation
dc.subjectsystem identification
dc.titleOn-line almost-sure parameter estimation for partially observed discrete-time linear systems with known noise characteristics
dc.typeJournal article
pubs.publication-statusPublished

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