Competing Behavior of Two Kinds of Self-Organizing Maps and Its Application to Clustering

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Description

The Self-Organizing Map (SOM) is an unsupervised neural network introduced in the 80's by Teuvo Kohonen. In this paper, we propose a method of simultaneously using two kinds of SOM whose features are different (the nSOM method). Namely, one is distributed in the area at which input data are concentrated, and the other self-organizes the whole of the input space. The competing behavior of the two kinds of SOM for nonuniform input data is investigated. Furthermore, we show its application to clustering and confirm its efficiency by comparing with the k-means method.

Journal

  • IEICE Trans. Fundamentals, A

    IEICE Trans. Fundamentals, A 90 (4), 865-871, 2007-04-01

    The Institute of Electronics, Information and Communication Engineers

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Keywords

Details 詳細情報について

  • CRID
    1570572702555847296
  • NII Article ID
    110007519145
  • NII Book ID
    AA10826239
  • ISSN
    09168508
  • Text Lang
    en
  • Data Source
    • CiNii Articles

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