多層競合ネットによる座標変換に不変なパターン認識 A Multi-Layered Competitive Net for Pattern Recognition Invariant to Coordinate Transformations

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A multi-layered competitive neural network is presented for learning to achieve pattern recognition in a manner invariant to linear and/or nonlinear coordinate transformations such as projection, shift, rotation, magnification and so on. The transformed input patterns stored in the network are multiplied by the Jacobian of the transformation, an aspect shown to be essential for the transformation invariance. The network also has excellent generalization ability as has been verified by computer simulation.

収録刊行物

  • 日本神経回路学会誌 = The Brain & neural networks

    日本神経回路学会誌 = The Brain & neural networks 7(4), 106-114, 2000-12-05

    Japanese Neural Network Society

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各種コード

  • NII論文ID(NAID)
    10008841723
  • NII書誌ID(NCID)
    AA11658570
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    1340766X
  • データ提供元
    CJP書誌  J-STAGE 
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