By Topic

A new adaptive algorithm for the generalized symmetric eigenvalue problem

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)
Abed-Meraim, K. ; TSI Dept., Telecom Paris, Paris ; Attallah, Samir

In this paper, we propose a new adaptive algorithm for the generalized symmetric eigenvalue problem, which can extract the principal and minor generalized eigenvectors, as well as their corresponding subspaces, at a low computational cost. This algorithm exploits the idea of reduced rank introduced by Davila et al (2000) which transforms the GED problem into a similar one but of reduced dimension that can easily be solved using conventional means. The proposed method is compared to the RLS algorithm by Yang et al (2006) and shown to outperform it w.r.t. both computational cost and convergence rate.

Published in:

Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on

Date of Conference:

12-15 Feb. 2007