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Winner-relaxing and winner-enhancing Kohonen maps: Maximal mutual information from enhancing the winner

Jens Christian Claussen
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Abstract

The magnification behaviour of a generalized family of self-organizing feature maps, the Winner Relaxing and Winner Enhancing Kohonen algorithms is analyzed by the magnification law in the one-dimensional case, which can be obtained analytically. The Winner-Enhancing case allows to acheive a magnification exponent of one and therefore provides optimal mapping in the sense of information theory. A numerical verification of the magnification law is included, and the ordering behaviour is analyzed. Compared to the original Self-Organizing Map and some other approaches, the generalized Winner Enforcing Algorithm requires minimal extra computations per learning step and is conveniently easy to implement.

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BibTeXRIS

Jens Christian Claussen. 2006-09-20. Winner-relaxing and winner-enhancing Kohonen maps: Maximal mutual information from enhancing the winner. https://doi.org/10.1002/cplx.10084

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