Abstract
Blind Source Separation (BSS) is a basic problem in signal processing. In this paper, we present a new method for separating convolutive mixtures based on the minimization of the output mutual information. We also introduce the concept of joint score function, and derive its relationship with marginal score function and independence. The new approach for minimizing the mutual information is very efficient, although limited by multivariate distribution estimations. © Springer-Verlag Berlin Heidelberg 2001.
Cite
CITATION STYLE
Babaie-Zadeh, M., Jutten, C., & Nayebi, K. (2001). Separating convolutive mixtures by mutual information minimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2085 LNCS, pp. 834–842). Springer Verlag. https://doi.org/10.1007/3-540-45723-2_101
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