Abstract
The problem of blind separation of statistically independent sources from instantaneous mixtures, using the efficient framework of independent component analysis (ICA), has been widely addressed in the literature. In this letter, the authors propose a sequential blind signal extraction algorithm that attempts to identify smooth sources in instantaneous mixtures. The approach incorporates smoothness constraints in the traditional negentropy cost function to extract smooth components, using an approximate second-order optimization method
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