多重化砂時計型ネットを用いた広いクラスの曲面によるデータフィッティング Data Fitting by a Broad Class of Surfaces Using Multiplied Bottleneck Networks

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Bottleneck networks were employed in order to estimate a low dimensional surface on which the high dimensional data lie. However, the fitting of closed surfaces like a sphere is hard for them. This is essentially due to the fact that general manifolds cannot be expressed by a single coordinate system. To overcome this difficulty, we multiply the bottleneck networks and construct a mixture of experts network, which can treat a broad class of surfaces. A procedure to restrain the premature convergence of the mixture of experts network is also provided.

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 5(1), 3-9, 1998-03-05

    Japanese Neural Network Society

参考文献:  8件中 1-8件 を表示

被引用文献:  1件中 1-1件 を表示

各種コード

  • NII論文ID(NAID)
    10008841350
  • 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  CJP引用  J-STAGE 
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