Adaptive RLS algorithm for blind source separation using a natural gradient

被引：40
|
作者：
Zhu, XL [1 ]
Zhang, XD
机构：
[1] Xidian Univ, Key Lab Radar Signal Proc, Xian 710071, Peoples R China
[2] Tsing Hua Univ, Dept Automat, State Key Lab Intellegent Technol & Syst, Beijing 100084, Peoples R China
来源：
IEEE SIGNAL PROCESSING LETTERS | 2002年 / 9卷 / 12期
关键词：
blind source separation; natural gradient; nonlinear principle component analysis; orthogonality constraint; recursive least squares; Stiefel manifold;
D O I：
10.1109/LSP.2002.806047
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：
By using the natural gradient on the Stiefel manifold to minimize a nonlinear principle component analysis criterion, this letter proposes a new adaptive recursive-least-squares (RLS) algorithm with prewhitening for blind source separation (BSS), which makes full use of the orthogonality constraint of the separating matrix. Simulations show that the new natural-gradient-based RLS algorithm has faster convergence than the existing least-mean-square algorithms and RLS algorithm for BSS.
引用
收藏
页码：432 / 435
页数：4
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