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  [in Japanese] Data Fitting by a Broad Class of Surfaces Using Multiplied Bottleneck Networks  [in Japanese]

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Author(s)

Abstract

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.

Journal

  • The Brain & Neural Networks

    The Brain & Neural Networks 5(1), 3-9, 1998-03-05

    Japanese Neural Network Society

References:  8

Cited by:  1

Codes

  • NII Article ID (NAID)
    10008841350
  • NII NACSIS-CAT ID (NCID)
    AA11658570
  • Text Lang
    JPN
  • Article Type
    Journal Article
  • ISSN
    1340766X
  • Data Source
    CJP  CJPref  J-STAGE 
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