DocumentCode
1402123
Title
Gradient of the log-likelihood ratio for infinite dimensional stochastic systems
Author
Leland, Robert P.
Author_Institution
Dept. of Electr. & Comput. Eng., Alabama Univ., Tuscaloosa, AL, USA
Volume
45
Issue
9
fYear
2000
fDate
9/1/2000 12:00:00 AM
Firstpage
1770
Lastpage
1774
Abstract
Using a covariance operator approach, we derive an expression for the log-likelihood ratio gradient for system parameter estimation for continuous-time infinite-dimensional stochastic systems. The gradient formula includes the smoother estimates and derivatives of system operators, with no derivatives of estimates or covariance operators. The unbounded operators typically found in partial differential equations limit how much the gradient formula can be simplified. A random heat equation is considered
Keywords
continuous time systems; distributed parameter systems; maximum likelihood estimation; partial differential equations; stochastic systems; covariance operator approach; infinite dimensional stochastic systems; log-likelihood ratio; random heat equation; unbounded operators; Automatic control; Control systems; Feedback; Maximum likelihood estimation; Nonlinear control systems; Predictive control; Predictive models; Robust control; Stability; Stochastic systems;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.880646
Filename
880646
Link To Document