DocumentCode :
1900149
Title :
A new RLS algorithm for blind separation of convolutive mixture
Author :
Lv, Qi ; Zhang, Xian-Da ; Jia, Ying
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
fYear :
2004
fDate :
18-21 July 2004
Firstpage :
422
Lastpage :
426
Abstract :
In this paper, we first present a new criterion for nonlinear principal component analysis (PCA) available for blind source separation (BSS) of convolutive mixture. Then we derive a novel recursive least square (RLS) algorithm for time-domain BSS. Although several existing methods of time-domain BSS can avoid the indeterminacy of permutation and gain which makes the BSS problem difficult in frequency domain, they generally converge slowly. The proposed new algorithm has fast convergence. The simulation results are presented to illustrate the effectiveness of our algorithm.
Keywords :
blind source separation; convergence of numerical methods; convolution; least squares approximations; nonlinear estimation; principal component analysis; recursive estimation; RLS algorithm; blind source separation; convolutive mixture; fast convergence; nonlinear PCA; permutation; principal component analysis; recursive least square; time-domain BSS; Blind source separation; Finite impulse response filter; Least squares approximation; Least squares methods; Principal component analysis; Resonance light scattering; Signal processing; Source separation; Sun; Time domain analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2004
Print_ISBN :
0-7803-8545-4
Type :
conf
DOI :
10.1109/SAM.2004.1502982
Filename :
1502982
Link To Document :
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