April 1, 1997

Infomax and maximum likelihood for blind source separation

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Abstract

Algorithms for the blind separation of sources can be derived from several different principles. This article shows that the infomax (information-maximization) principle is equivalent to the maximum likelihood. The application of the infomax principle to source separation consists of maximizing an output entropy.

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J.-F. Cardoso (Tue,) studied this question.

synapsesocial.com/papers/6a11ceeeed9c06332dfd3fae https://doi.org/https://doi.org/10.1109/97.566704

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3A Non-linear Information Maximisation Algorithm that Performs Blind Separation1994 · 31 citations
4Blind separation of mixture of independent sources through a quasi-maximum likelihood approach1997 · 465 citations
5Temporal decorrelation using teacher forcing anti-Hebbian learning and its application in adaptive blind source separation2002 · 7 citations

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