Learning Method of Parameters for Fuzzy Rules in Universal Learning Network

DOI HANDLE Open Access
  • Ikeuchi Mitsuo
    Department of Energy conversion engineering, Kyushu University : Master's Program
  • Hirasawa Kotaro
    Department of Electrical and Electronic Systems Engineering, Kyushu University
  • Ohbayashi Masanao
    Department of Electrical and Electronic Systems Engineering, Kyushu University
  • Hu Jinglu
    :Department of Electrical and Electronic Systems Engineering, Kyushu University
  • Murata Junichi
    Department of Electrical and Electronic Systems Engineering, Kyushu University

Bibliographic Information

Other Title
  • 一般化学習ネットワークにおけるファジィルールを用いたパラメータの学習方式

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Abstract

In this paper, a new method which can alter the values of the parameters in neural networks is proposed in order to enhance the representation abilities of the networks. As an example, a fuzzy reference network is used to modify the parameters in this article, even though any kind of networks such as radial basis function networks and neural networks can be adopted to realize varying parameters. From simulations, it is shown that the network using the proposed method is better than the conventional neural networks in terms of representation abilities of the networks.

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Details 詳細情報について

  • CRID
    1390290699820221952
  • NII Article ID
    110000579895
  • NII Book ID
    AN10569524
  • DOI
    10.15017/1498361
  • ISSN
    21880891
    13423819
  • HANDLE
    2324/1498361
  • Text Lang
    ja
  • Data Source
    • JaLC
    • IRDB
    • CiNii Articles
  • Abstract License Flag
    Allowed

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