Please use this identifier to cite or link to this item: https://doi.org/10.1109/ISSPA.2007.4555621
Title: A new adaptive algorithm for the generalized symmetric eigenvalue problem
Authors: Abed-Meraim, K.
Attallah, S. 
Issue Date: 2007
Source: Abed-Meraim, K.,Attallah, S. (2007). A new adaptive algorithm for the generalized symmetric eigenvalue problem. 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings : -. ScholarBank@NUS Repository. https://doi.org/10.1109/ISSPA.2007.4555621
Abstract: 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. ©2007 IEEE.
Source Title: 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/68910
ISBN: 1424407796
DOI: 10.1109/ISSPA.2007.4555621
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

1
checked on Dec 11, 2017

Page view(s)

20
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.