Multi-channel signal separation by decorrelation

Author

Weinstein, Ehud ; Feder, Meir ; Oppenheim, Alan V.

Author_Institution

Dept. of Electr. Eng., Tel Aviv Univ., Israel

Volume

1

Issue

4

fYear

1993

fDate

10/1/1993 12:00:00 AM

Firstpage

405

Lastpage

413

Abstract

Identification of an unknown system and recovery of the input signals from observations of the outputs of an unknown multiple-input, multiple-output linear system are considered. Attention is focused on the two-channel case, in which the outputs of a 2×2 linear time invariant system are observed. The approach consists of reconstructing the input signals by assuming that they are statistically uncorrelated and imposing this constraint on the signal estimates. In order to restrict the set of solutions, additional information on the true signal generation and/or on the form of the coupling systems is incorporated. Specific algorithms are developed and tested. As a special case, these algorithms suggest a potentially interesting modification of Widrow´s (1975) least-squares method for noise cancellation, where the reference signal contains a component of the desired signal

Keywords

filtering and prediction theory; least squares approximations; signal processing; 2×2 linear time invariant system; coupling systems; decorrelation; input signals; least-squares method; multichannel signal separation; noise cancellation; signal estimates; signal generation; two-channel case; unknown multiple-input multiple-output linear system; Background noise; Decorrelation; Least squares methods; Linear systems; Loudspeakers; MIMO; Sensor systems; Signal processing; Source separation; Speech enhancement;

fLanguage

English

Journal_Title

Speech and Audio Processing, IEEE Transactions on

Publisher

ieee

ISSN

1063-6676

Type

jour

DOI

10.1109/89.242486

Filename

242486