Abstract
This paper discusses the problems raised by the optimization of a mutual information-based objective function, in the context of a multimodal speaker detection. As no approximation is used, this function is highly nonlinear and plagued by numerous local minima. Three different optimization methods are compared. The Differential Evolution algorithm is deemed to be the best for the problem at hand and, consequently, is used to perform the speaker detection.
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© 2006 Springer-Verlag Berlin Heidelberg
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Besson, P., Vesin, JM., Popovici, V., Kunt, M. (2006). Differential Evolution Applied to a Multimodal Information Theoretic Optimization Problem. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_46
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DOI: https://doi.org/10.1007/11732242_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33237-4
Online ISBN: 978-3-540-33238-1
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