Zero-entropy minimization for blind extraction of bounded sources (BEBS)
(2006) Independent Component Analysis and Blind Signal Sepration, ICA 2006 — ISBN: [3-540-32630-8], 747-754, published
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- Renyi's entropy can be used as a cost function for blind source separation (BSS). Previous works have emphasized the advantage of setting Renyi's exponent to a value different from one in the context of BSS. In this paper, we focus on zero-order Renyi's entropy minimization for the blind extraction of bounded sources (BEBS). We point out the advantage of choosing the extended zero-order Renyi's entropy as a cost function in the context of BEBS, when the sources have non-convex supports.
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Vrins, F., Erdogmus, D., Jutten, C., & Verleysen, M. (2006). Zero-entropy minimization for blind extraction of bounded sources (BEBS). In J. Rosca, D. Erdogmus, J. Principe and S. Haykin (ed.), Independent Component Analysis and Blind Signal Sepration, ICA 2006 (pp. 747-754). Springer-Verlag. https://doi.org/10.1007/11679363_93