A Fast Adaptive Algorithm for the Generalized Symmetric Eigenvalue Problem

被引：32

作者：

Attallah, Samir ^{[1
]}

Abed-Meraim, Karim ^{[2
]}

机构：

[1] SIM Univ, Sch Sci & Technol, Singapore 599490, Singapore

[2] ENST Telecom Paris, TSI Dept, Paris, France

来源：

IEEE SIGNAL PROCESSING LETTERS | 2008年 / 15卷

关键词：

Adaptive algorithm; fast estimation and tracking; generalized eigenvalue problem; generalized eigenvectors; generalized subspace estimation;

D O I：

10.1109/LSP.2008.2006346

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this letter, 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. A comparison with other adaptive algorithms from the literature, including the batch generalized singular value decomposition (GSVD) technique, is also given to show the superiority of the proposed algorithm in terms of convergence performance and computational complexity.

引用

页码：797 / 800

页数：4

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