DocumentCode :
822633
Title :
Efficient computation of gradient and hessian of likelihood function in linear dynamic systems
Author :
Gupta, Narendra K.
Author_Institution :
Systems Control, Incorporated, Palo Alto, CA, USA
Volume :
21
Issue :
5
fYear :
1976
fDate :
10/1/1976 12:00:00 AM
Firstpage :
781
Lastpage :
783
Abstract :
This technical note describes a computationally efficient procedure to determine the first and second gradients of the likelihood function for parameter estimation in linear dynamic systems. The results presented here are extensions, of the sensitivity functions reduction procedure of [1]. An operation count shows the value of the new algorithm.
Keywords :
Linear systems, stochastic continuous-time; Parameter estimation; maximum-likelihood (ML) estimation; Automatic control; Autoregressive processes; Control systems; Difference equations; H infinity control; Least squares methods; Linear systems; Maximum likelihood estimation; Parameter estimation; Stochastic processes;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1976.1101359
Filename :
1101359
Link To Document :
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