DocumentCode
2614717
Title
Blind source separation of convolutive mixtures
Author
Servière, C.
Author_Institution
CEPHAG-ENSIEG, Saint-Martin d´´Heres, France
fYear
1996
fDate
24-26 Jun 1996
Firstpage
316
Lastpage
319
Abstract
When a priori information about the propagation or the geometry of the array are not available, the model can be generalized to a blind source separation problem. It supposes the statistical independence of the sources and their non-Gaussianity. The observed signals are assumed to be convolutive mixtures of wide-band sources. Several criteria of source separation are studied which are based on the cancellation of different fourth-order cross-cumulants. For these criteria, we show in which conditions the separation is achieved. Results on real data illustrate the proposed methods
Keywords
array signal processing; convolution; higher order statistics; array geometry; array signal processing; blind source separation; convolutive mixtures; fourth-order cross-cumulants cancellation; nonGaussian sources; observed signals; propagation; statistical source independence; wideband sources; Blind source separation; Covariance matrix; Digital communication; Geometry; Matrix decomposition; Multipath channels; Sensor arrays; Solid modeling; Source separation; Wideband;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal and Array Processing, 1996. Proceedings., 8th IEEE Signal Processing Workshop on (Cat. No.96TB10004
Conference_Location
Corfu
Print_ISBN
0-8186-7576-4
Type
conf
DOI
10.1109/SSAP.1996.534880
Filename
534880
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