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This paper focuses on blind source separation with an unknown number of sources, which is the case generally assumed in most practical applications. Several over-determined neural algorithms (more sensors m than sources n) have been proposed to solve the problems associated with these cases, but separating performance is often sacrificed in order to prevent divergence. The general natural gradient...
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