DocumentCode :
837554
Title :
Derivative computations for the log likelihood function
Author :
Wilson, David A. ; Kumar, Alok
Author_Institution :
University of Leeds, Leeds, England
Volume :
27
Issue :
1
fYear :
1982
fDate :
2/1/1982 12:00:00 AM
Firstpage :
230
Lastpage :
232
Abstract :
This note improves on a method for computing derivatives of the log likelihood function used in the identification of discrete, linear time-invariant Gaussian systems. A formula for the derivative is obtained in terms of the derivatives of the matrices used to define the system under identification.
Keywords :
Gaussian processes; Linear systems, stochastic; Stochastic systems, linear; System identification, linear systems; maximum-likelihood (ML) estimation; Kalman filters; Riccati equations;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1982.1102834
Filename :
1102834
Link To Document :
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