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