Blind separation of instantaneous mixture of sources based on orderstatistics

Authors:
D.-T. Pham
Affiliations:
Lab. of Modeling & Computation, CNRS, Grenoble
Venue:
IEEE Transactions on Signal Processing
Year:
2000

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Abstract

In this paper, we introduce a novel procedure for separating an instantaneous mixture of sources based on order statistics. The method is derived in a general context of independence component analysis, using a contrast function defined in term of the Kullback-Leibler divergence or of the mutual information. We introduce a discretized form of this contrast permitting its easy estimation through order statistics. We show that the local contrast property is preserved and derive a global contrast, exploiting only the information of the support of the distribution (in case this support is finite). Some simulations are given, illustrating the good performance of the method