DocumentCode :
3178753
Title :
Multi-channel blind signal separation by decorrelation
Author :
Chan, Dominic C B ; Rayner, Peter J W ; Godsill, Simon J.
Author_Institution :
Dept. of Eng., Cambridge Univ., UK
fYear :
1995
fDate :
15-18 Oct 1995
Firstpage :
155
Lastpage :
158
Abstract :
The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and crosstalk in data communications. We propose iterative algorithms to solve the n×n linear time invariant system under two different constraints. Some existing solutions for 2×2 systems are reviewed and compared
Keywords :
MIMO systems; correlation methods; iterative methods; linear systems; signal processing; speech processing; telecommunication channels; EEG signals; acoustic environment; background noise; crosstalk; data communications; decorrelation; independent sources separation; iterative algorithms; linear mixtures; linear multiinput multioutput system; linear time invariant system; mixed observed data; multichannel blind signal separation; passive sonar applications; source signals; speech recordings; Background noise; Blind source separation; Brain modeling; Crosstalk; Data communication; Decorrelation; Electroencephalography; Loudspeakers; Sonar applications; Speech enhancement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Signal Processing to Audio and Acoustics, 1995., IEEE ASSP Workshop on
Conference_Location :
New Paltz, NY
Print_ISBN :
0-7803-3064-1
Type :
conf
DOI :
10.1109/ASPAA.1995.482980
Filename :
482980
Link To Document :
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