Art

J-GLOBAL ID：200902177070335670   Reference number：01A0353305

Nonlinear Principal Component Analysis by Learning Nerve Fields United by Inhibitory Connections.

抑制性結合で結ばれた複数の学習神経場による非線形主成分分析

Author (2)： SHIRAKURA JUN (大阪大 大学院基礎工学研究科) ,  KURATA KOJI (琉球大 工)
Material： 電子情報通信学会論文誌 D-2  (IEICE Transactions on Information and Systems, Pt.2 (Japanese Edition))
Volume： J84-D-2  Issue： 3  Page： 549-558  Publication year： Mar. 01, 2001 
JST Material Number： L0197A  ISSN： 0915-1923  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： JAPANESE (JA)

Thesaurus term： *self-organizing feature map ,...
Semi thesaurus term： neural field ,...

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JST classification (2)： Brain and nervous system models  (EL02050C) ,  Artificial intelligence  (JE08000Z)

Reference (14)：

• TAKEUCHI, A. Formation of topographic maps and columnar microstructures. Biol. Cybern. 1979, 35, 63-72
• AMARI, S. Topographic organization of nerve fields. Bulletin of Mathematical Biology. 1980, 42, 339-364
• FUKUSHIMA, K. Cognitron: A self-organizing multilayered neural network. Biol. Cybern. 1975, 20, 121-136
• FUKUSHIMA, K. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol. Cybern. 1980, 36, 193-202
• KOHONEN, T. Self-organized formation of topologically correct feature map. Biol. Cybern. 1982, 43, 59-69

Terms in the title (3)： 学習 ,  神経 ,  非線形主成分分析