Blind source separation via the second characteristic function with asymptotically optimal weighting

Abstract

Blind source separation (BSS) is the problem of reconstructing unobserved, statistically independent source signals from observed linear combinations thereof. An emerging tool for BSS is the second generalized characteristic function (SGCF), as demonstrated, e.g., by the characteristic-function enabled source separation (CHESS) algorithm (Yeredor (2000… (More)

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