DocumentCode
834305
Title
Identification and model approximation for continuous-time systems on finite parameter sets
Author
Tugnait, Jitendra K.
Author_Institution
University of Iowa, Iowa City, IA, USA
Volume
25
Issue
6
fYear
1980
fDate
12/1/1980 12:00:00 AM
Firstpage
1202
Lastpage
1206
Abstract
Almost-sure convergence of the maximum likelihood and the maximum a posteriori probability estimates of unknown parameters of continuous-time stochastic dynamical linear time-invariant systems is investigated. The unknown parameter set is assumed to be finite. The situation where the ture parameter does not belong to the unknown parameter set is considered, as well as the situation where the true model is included in the unknown parameter set.
Keywords
Linear systems, stochastic continuous-time; MAP estimation; Parameter identification; maximum-likelihood (ML) estimation; Character generation; Convergence; Covariance matrix; Maximum likelihood estimation; Parameter estimation; Q measurement; Riccati equations; Stochastic systems; Sufficient conditions; Vectors;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.1980.1102519
Filename
1102519
Link To Document