DocumentCode
1051784
Title
A stochastic estimation algorithm with observation averaging
Author
Juditsky, Anatoli
Author_Institution
IRISA/INRIA, Rennes, France
Volume
38
Issue
5
fYear
1993
fDate
5/1/1993 12:00:00 AM
Firstpage
794
Lastpage
798
Abstract
An algorithm for the constrained problem of estimating the regression coefficients is presented. The algorithm is based on the idea of direct averaging of the observations in order to estimate the search direction. It is shown that if the true parameter belongs to the permitted set, then the algorithm delivers asymptotically optimal estimates of the parameter. Finite convergence of the method is proved when the true parameter lies outside the permitted set
Keywords
estimation theory; observability; parameter estimation; asymptotically optimal estimates; constrained problem; direct averaging; observation averaging; regression coefficients; search direction; stochastic estimation algorithm; true parameter; Algorithm design and analysis; Automatic control; Control systems; Filtering theory; Linear systems; MATLAB; Stochastic processes; Sufficient conditions; Vectors;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.277249
Filename
277249
Link To Document