誤差逆伝播学習法による自己組織化ロバスト主成分分析  [in Japanese] Self-Organized Robust Principal Component Analysis by Back-Propagation Learning  [in Japanese]

Abstract

The purpose of this study is the suggestion of a self-organized back-propagation algorithm for robust principal component analysis. The self-organizing algorithm that discriminates the influence of data automatically is applied to learning of a sandglass type neural network.

The purpose of this study is the suggestion of a self-organized back-propagation algorithm for robust principal component analysis. The self-organizing algorithm that discriminates the influence of data automatically is applied to learning of a sandglass type neural network.

Journal

広島大学大学院工学研究科研究報告   [List of Volumes]

広島大学大学院工学研究科研究報告 53(1), 1-4, 2004-12  [Table of Contents]

Hiroshima University

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Codes

  • NII Article ID (NAID) :
    110004708319
  • NII NACSIS-CAT ID (NCID) :
    AA11700032
  • Text Lang :
    JPN
  • Article Type :
    Departmental Bulletin Paper
  • Journal Type :
    大学紀要
  • ISSN :
    00182060
  • NDL Article ID :
    7223933
  • NDL Source Classification :
    ZM2(科学技術--科学技術一般--大学・研究所・学会紀要)
  • NDL Call No. :
    Z14-44
  • Databases :
    NDL  NII-ELS  IR