By Topic

Approximate diagonalization approach to blind source separation with a subset of 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

2 Author(s)
Tome, A.M. ; DETUA, Aveiro Univ., Portugal ; Lang, E.W.

In blind source separation problems it is assumed that the approximate diagonalization of a matrix set achieves more robust solutions than the simultaneous diagonalization of a matrix pencil. In this work we will analyse approximate diagonalization methods using a generalized eigendecomposition (GED) of any pair of a given matrix set. The constraints of GHD solutions provide a criterion to choose a matrix subset even when none of the matrices follows an ideal model. We also present some numerical simulations comparing the performance of the solutions achieved by the referred approaches.

Published in:

Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on  (Volume:2 )

Date of Conference:

1-4 July 2003