DocumentCode
1313531
Title
Sequential algorithms for parameter estimation based on the Kullback-Leibler information measure
Author
Weinstein, Ehud ; Feder, Meir ; Oppenheim, Alan V.
Author_Institution
Dept. of Electr. Eng.-Syst., Tel-Aviv Univ., Israel
Volume
38
Issue
9
fYear
1990
fDate
9/1/1990 12:00:00 AM
Firstpage
1652
Lastpage
1654
Abstract
Methods of stochastic approximation are used to convert iterative algorithms for maximizing the Kullback-Leibler information measure into sequential algorithms. Special attention is given to the case of incomplete data, and several algorithms are presented to deal with situations of this kind. The application of these algorithms to the identification of finite impulse response systems is considered
Keywords
information theory; parameter estimation; stochastic processes; Kullback-Leibler information measure; finite impulse response systems; incomplete data; iterative algorithms; parameter estimation; sequential algorithms; stochastic approximation; Algorithm design and analysis; Approximation algorithms; Convergence; Finite impulse response filter; Iterative algorithms; Maximum likelihood estimation; Parameter estimation; Sea measurements; Signal processing algorithms; Stochastic processes;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/29.60089
Filename
60089
Link To Document