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Dynamics of self-organized feature mapping

  • R. Der
  • Th. Villmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 686)

Abstract

The dynamics of the feature maps created by Kohonen's algorithm is studied by analyzing the spectral density of synaptic fluctuations both analytically and by means of computer simulations. We consider unsupervised learning as a stochastic process and investigate the usefulness of the Fokker-Planck approach for the case of a topological mismatch between input and output space. A breakdown of the Fokker-Planck description is observed if the mismatch exceeds a critical value.

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References

  1. [1]
    H. Ritter, T. Martinetz, K. Schulten: Neural Computation and Self-organizing Maps. Reading (Mass.): Addison-Wesley, 1992.Google Scholar
  2. [2]
    T. Kohonen: Self-Organization and Associative Memory. Springer Series in Information Science 8, Berlin, Heidelberg: Springer-Verlag, 1984.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • R. Der
    • 1
  • Th. Villmann
    • 1
  1. 1.Institut für InformatikUniversität LeipzigLeipzig

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