Abstract
It has been well known that edge filters in the visual system can be generated by the InfoMax principle. In this paper, the “InfoMin” principle is proposed, which asserts that the information through some neighboring signals on a two-dimensional mapping must be minimized. It is shown that the standard Comon’s ICA can be derived from the combination of the InfoMax principle for the whole signals and the InfoMin one for each signal under a linear model with sufficiently large noise. It is also shown that the InfoMin principle for the signals within neighboring areas can generate a topographic mapping in the same way as in topographic ICA.
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© 2006 Springer-Verlag Berlin Heidelberg
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Matsuda, Y., Yamaguchi, K. (2006). The InfoMin Principle for ICA and Topographic Mappings. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_119
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DOI: https://doi.org/10.1007/11679363_119
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32630-4
Online ISBN: 978-3-540-32631-1
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