Kohonen's self-organizing maps: Exploring their computational capabilities

Helge Ritter, Klaus Schulten

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The authors demonstrate that the computational capabilities of Kohonen's algorithm provide an unified approach to such diverse fields as sensory mappings, combinatorial optimization, and learning in motor control. For a discrete probability distribution of the training inputs, the formation of the mapping can be described as a probabilistic descent in a potential. In view of their wide applicability, the principles of the algorithm might also be inherent to the maturation of biological brains and could help to achieve a better understanding of these processes from a more unified point of view.

Original languageEnglish (US)
Title of host publicationIEEE Int Conf on Neural Networks
PublisherPubl by IEEE
Pages109-116
Number of pages8
StatePublished - 1988

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Ritter, H., & Schulten, K. (1988). Kohonen's self-organizing maps: Exploring their computational capabilities. In IEEE Int Conf on Neural Networks (pp. 109-116). Publ by IEEE.