Winner-relaxing self-organizing maps

Jens Christian Claussen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


A new family of self-organizing maps, the winner-relaxing Kohonen algorithm, is introduced as a generalization of a variant given by Kohonen in 1991. The magnification behavior is calculated analytically. For the original variant, a magnification exponent of 4/7 is derived; the generalized version allows steering the magnification in the wide range from exponent 1/2 to 1 in the one-dimensional case, thus providing optimal mapping in the sense of information theory. The winner-relaxing algorithm requires minimal extra computations per learning step and is conveniently easy to implement.

Original languageEnglish
Pages (from-to)996-1009
Number of pages14
JournalNeural Computation
Issue number5
Publication statusPublished - 1 May 2005


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