DocumentCode :
968136
Title :
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
Link To Document :
بازگشت