A penalized mutual information criterion for blind separation of convolutive mixtures

被引：13

作者：

El Rhabi, M ^{[1
]}

Gelle, G ^{[1
]}

Fenniri, H ^{[1
]}

Delaunay, G ^{[1
]}

机构：

[1] URCA, Fac Sci, Dept EEA, DeCom, F-51687 Reims 2, France

来源：

SIGNAL PROCESSING | 2004年 / 84卷 / 10期

关键词：

blind source separation; independent component analysis; convolutive mixtures; mutual information; penalized algorithm;

D O I：

10.1016/j.sigpro.2004.06.015

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：

The blind separation problem of linear time-dependent mixtures is addressed in this paper. We have developed a new algorithm based on the minimization of the mutual information as well as a penalized term which ensures an a priori normalization of the estimated sources (outputs) and so, avoids the scale indeterminacy. The criterion minimization is done using a well-known gradient approach. Finally, some numerical results are shown to illustrate the performance of the penalized algorithm compared to the Babaie-Zadeh approach presented in (Proceedings of IWANN, Granada, Spain, June 2001, pp. 834-842). (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：1979 / 1984

页数：6