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Cybernetics and Systems Analysis

, Volume 49, Issue 3, pp 366–374 | Cite as

Adaptive fuzzy clustering with a variable fuzzifier

  • B. V. Kolchygin
  • Ye. V. Bodyanskiy
Article

Abstract

The problem of fuzzy clustering of multivariate observations is considered and a group of Kohonen neural network adaptive self-learning algorithms is proposed. The algorithms allow for online possibilistic fuzzy clustering with variable fuzziness levels and are computationally simple and flexible when operating under a priori uncertainty about the nature of data distribution in clusters.

Keywords

fuzzy clustering fuzzifier Kohonen neural network self-learning algorithm 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Kharkov National University of Radio ElectronicsKharkovUkraine

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