Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/45124

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Title
Parameter estimation for discrete-time nonlinear systems using EM
Author/Creator
Wills, Adrian;  Schon, Thomas B.;  Ninness, Brett
Institution
The University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science
Description
In this paper we consider parameter estimation of general stochastic nonlinear statespace models using the Maximum Likelihood method. This is accomplished via the employment of an Expectation Maximisation algorithm, where the essential components involve a particle smoother for the expectation step, and a gradient-based search for the maximisation step. The utility of this method is illustrated with several nonlinear and non-Gaussian examples.
Relation
17th World Congress of the International Federation of Automatic Control. Proceedings of the 17th World Congress of the International Federation of Automatic Control (Seoul, Korea 6-11 July, 2008) p. 4012-4017
Relation
http://www.ifac-papersonline.net/Detailed/36391.html
Date
2008
Publisher
International Federation of Automatic Control (IFAC)
Keyword(s)
nonlinear estimation;  maximum likelihood;  system identification;  expectation
Resource Type
conference paper
Identifier
http://hdl.handle.net/1959.13/45124
Identifier
ISBN:9781123478902
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Subject
"Parameter estimation for discrete-time nonlinear systems using EM"
 
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