DocumentCode :
1856469
Title :
Multi-channel signal separation
Author :
Chan, Dominic C B ; Rayner, Peter J W ; Godsill, Simon J.
Author_Institution :
Dept. of Eng., Cambridge Univ., UK
Volume :
2
fYear :
1996
fDate :
7-10 May 1996
Firstpage :
649
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 cross-talk 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; acoustic noise; acoustic signal processing; iterative methods; linear systems; speech processing; telecommunication channels; EEG signals; acoustic environment; background noise; competing speakers; crosstalk; data communications; independent sources separation; iterative algorithms; linear mixtures; linear multiinput multioutput system; linear time invariant system; mixed observed data; multichannel signal separation; passive sonar applications; source signals; speech recordings; Background noise; Brain modeling; Data communication; Electroencephalography; Iterative algorithms; Loudspeakers; Sonar applications; Source separation; Speech enhancement; Time invariant systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1520-6149
Print_ISBN :
0-7803-3192-3
Type :
conf
DOI :
10.1109/ICASSP.1996.543204
Filename :
543204
Link To Document :
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