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Paper data
New contrasts for blind separation of non iid sources in the convolutive case

Castella Marc, IGM and URA-CNRS 820
Pesquet Jean-Christophe, IGM and URA-CNRS 820
Petropulu Athina P., ECE Department, Drexel University

Page numbers in the proceedings:
Volume II pp 107-110

Blind Identification and Deconvolution

Paper abstract
This paper deals with the separation of convolutive mixtures of independent source signals. Starting from a frequency point of view, we consider a joint diagonalization criterion. Integration of the latter over the frequency domain leads to contrasts which are valid for both iid and non iid sources. A generalization of these contrasts is proposed: it aims at obtaining contrasts with improved statistical performances. A link with existing time-domain contrasts is established. A simple gradient based method for the optimization of the contrasts is proposed and evaluated through simulation tests.

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