Title :
Maximum entropy and robust prediction on a simplex
Author :
Poor, H. Vincent
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
fDate :
5/1/1999 12:00:00 AM
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;
Journal_Title :
Information Theory, IEEE Transactions on
