Art

J-GLOBAL ID：200902142727943600   Reference number：99A0435356

A Formulation of Learning Vector Quantization Using a New Misclassification Measure.

新しい誤分類尺度を用いた学習ベクトル量子化の定式化

Author (2)： SATO ATSUSHI (NEC C&Cメディア研) ,  YAMADA KEIJI (NEC C&Cメディア研)
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： J82-D-2  Issue： 4  Page： 650-659  Publication year： Apr. 25, 1999 
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： *learning ,...

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JST classification (2)： Pattern recognition  (JE07000S) ,  Artificial intelligence  (JE08000Z)

Reference (14)：

• KOHONEN, T. Self-Organizing Maps. 1995
• SONG, H. H. LVQ combined with simulated annealing for optimal design of large-set reference models. Neural Networks. 1996, 9, 2, 329-336
• AMARI, S. A theory of adaptive pattern classifiers. IEEE Trans. Elec. Comput. 1967, EC-16, 299-307
• KATAGIRI, S. New discriminative training algorithms based on the generalized probabilistic descent method. Proc. of IEEE Workshop on Neural Netrowks for Signal Processing. 1991, 299-308
• JUANG, B. -H. Discriminative learning for minimum error classification. IEEE Trans. on Signal Processing. 1992, 40, 12, 3043-3054

Terms in the title (4)： 分類 ,  尺度 ,  学習ベクトル量子化 ,  定式化