Pruning Rule for kMER-Based Acquisition of the Global Topographic Feature Map(Biocybernetics, Neurocomputing)

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概要

• 論文の詳細を見る

• For a kernel-based topographic map formation, kMER (kernel-based maximum entropy learning rule) was proposed by Van Hulle, and some effective learning rules related to kMER have been proposed so far with many applications. However, no discusions have been made concerning the determination of the number of units in kMER. This letter describes a unit-pruning rule, which permits automatic contruction of an appropriate-sized map to acquire the global topographic features underlying the input data. The effectiveness and the validity of the present rule have been confirmed by some preliminary computer simulations.

• 社団法人電子情報通信学会の論文
• 2005-03-01

著者

• Uchino Eiji

  The Authors Are With The Department Of Physics Biology And Informatics Faculty Of Science Yamaguchi

• Suetake Noriaki

  The Authors Are With The Department Of Physics Biology And Informatics Faculty Of Science Yamaguchi

• ISHIGAKI Chuhei

  The authors are with the Department of Physics, Biology and Informatics, Faculty of Science, Yamaguc

• Ishigaki Chuhei

  The Authors Are With The Department Of Physics Biology And Informatics Faculty Of Science Yamaguchi

関連論文

• Pruning Rule for kMER-Based Acquisition of the Global Topographic Feature Map(Biocybernetics, Neurocomputing)

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