Convolutive Blind Signal Separation Based on Asymmetrical Contrast Functions

Abstract

In this paper, we consider the blind signal separation problem for convolutive mixtures, in the real case. More precisely, we present a generalization of classical contrast functions to more flexible asymmetric forms. We provide several examples of these new criteria which are useful for sources having different high-order statistics. We also perform a statistical study of the proposed source separation approach, including both the consistency and the asymptotic normality aspects. These theoretical results are also confirmed by numerical simulations