DocumentCode
1929414
Title
Finite dimensional filters for maximum likelihood estimation of continuous-time linear Gaussian systems
Author
Elliott, Robert J. ; Krishnamurthy, Vikram
Author_Institution
Dept. of Math. Sci., Alberta Univ., Edmonton, Alta., Canada
Volume
5
fYear
1997
fDate
10-12 Dec 1997
Firstpage
4469
Abstract
We derive a new class of finite dimensional filters for integrals and stochastic integrals of moments of the state for continuous-time linear Gaussian systems. Apart from being of significant mathematical interest, these new filters can be used with the expectation maximization algorithm to yield maximum likelihood estimates of the model parameters
Keywords
Kalman filters; continuous time systems; filtering theory; maximum likelihood estimation; probability; stochastic systems; Kalman filter; continuous-time systems; expectation maximization algorithm; finite dimensional filters; linear Gaussian systems; maximum likelihood estimation; parameter estimation; probability space; stochastic integrals; stochastic systems; Information processing; Integral equations; Maximum likelihood estimation; Nonlinear filters; Parameter estimation; Riccati equations; Signal processing; Signal processing algorithms; Stochastic systems; Yttrium;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location
San Diego, CA
ISSN
0191-2216
Print_ISBN
0-7803-4187-2
Type
conf
DOI
10.1109/CDC.1997.649670
Filename
649670
Link To Document