By Topic

On the uniqueness of the maximum-likeliwood estimate of structured covariance matrices

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)
Nguyen /A/. ; Technical University of Budapest, Budapest, Hungary

A generalized Burg technique has been developed recently by Burg, Luenberger, and Wenger for maximum likelihood estimation of structured covariance matrices. Uniqueness of the estimate in the restricted subset of the class of nonnegative definite symmetric matrices is not known. In this paper it is shown that the positive definite estimate over the class of nonnegative definite, doubly symmetric (symmetric about both the main and minor diagonals) matrices is unique. Moreover, if the minor diagonal symmetrized version of the sample covariance matrix is nonsingular, it is the unique estimate. If the minor diagonal symmetrized sample covariance matrix is singular and a positive definite estimate exists, then the estimate is unique.

Published in:

Acoustics, Speech and Signal Processing, IEEE Transactions on  (Volume:32 ,  Issue: 6 )