By Topic

Maximum entropy and robust prediction on a simplex

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Poor, H.V. ; Dept. of Electr. Eng., Princeton Univ., NJ, USA

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

Published in:

Information Theory, IEEE Transactions on  (Volume:45 ,  Issue: 4 )