DocumentCode
1502137
Title
Maximum entropy and robust prediction on a simplex
Author
Poor, H. Vincent
Author_Institution
Dept. of Electr. Eng., Princeton Univ., NJ, USA
Volume
45
Issue
4
fYear
1999
fDate
5/1/1999 12:00:00 AM
Firstpage
1150
Lastpage
1164
Abstract
The related problems of (finite-length) robust prediction and maximizing spectral entropy over a simplex of covariance matrices are considered. General properties of iterative solutions of these problems are developed, and monotone convergence proofs are presented for two algorithms that provide such solutions. The analogous problems for simplexes of spectral densities are also considered
Keywords
convergence of numerical methods; covariance matrices; maximum entropy methods; minimax techniques; prediction theory; spectral analysis; algorithms; covariance matrices; finite-length robust prediction; iterative solutions; maximum entropy; minimax robust prediction; monotone convergence proofs; simplex; spectral densities; spectral entropy; Centralized control; Covariance matrix; Entropy; Helium; Iterative algorithms; Minimax techniques; Predictive models; Robustness; Stochastic processes; Uncertainty;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.761257
Filename
761257
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