Adaptive blind separation of independent sources: a second-order stable algorithm for the general case

Author

Delfosse, Nathalie ; Loubaton, Philippe

Author_Institution

Lille I Univ., Villeneuve d´´Ascq, France

Volume

47

Issue

7

fYear

2000

fDate

7/1/2000 12:00:00 AM

Firstpage

1056

Lastpage

1071

Abstract

In this paper, the adaptive separation of convolutive mixtures of independent sources is addressed. The case where the number of sensors is strictly greater than the number of sources is considered. Under a mild assumption on the unknown transfer function, it is shown that the separation can be nearly achieved by a three-step procedure: a linear prediction algorithm in the singular case; a separation of an instantaneous mixture; and the implementation of the inverse of the prediction filter. The main difficulty of this approach is to control the stability of this IIR filter. For that purpose, we use a normalized lattice structure, which is stable for any choice of its parameters

Keywords

IIR filters; adaptive filters; adaptive signal processing; filtering theory; lattice filters; prediction theory; stability; IIR filter stability; adaptive blind separation; convolutive mixtures; general case; independent sources; instantaneous mixture separation; linear prediction algorithm; normalized lattice structure; prediction filter inverse; second-order stable algorithm; singular case; three-step procedure; Adaptive filters; Finite impulse response filter; IIR filters; Lattices; Nonlinear filters; Prediction algorithms; Signal processing; Source separation; Stability; Transfer functions;

fLanguage

English

Journal_Title

Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on

Publisher

ieee

ISSN

1057-7122

Type

jour

DOI

10.1109/81.855461

Filename

855461