A Pattern Classifier-Modified AFC, and Handwritten Digit Recognition
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概要
- 論文の詳細を見る
We modified the adaptive fuzzy classification algorithm (AFC), which allows fuzzy clusters to grow to meet the demands of a given task during training. Every fuzzy cluster is defined by a reference vector and a fuzzy cluster radius, and it is represented as a shape of hypersphere in pattern space. Any pattern class is identified by overlapping plural hyperspherical fuzzy clusters so that it is possible to approximate complex decision boundaries among pattern classes. The modified AFC was applied to recognize handwritten digits, and performances were shown compared with other neural networks.
- 社団法人電子情報通信学会の論文
- 1994-10-25
著者
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SHIMIZU Eiji
Faculty of Engineering, Osaka City University
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Takahashi H
The Authors Are With Graduate School Of Information Science And Engineering Tokyo Institute Of Techn
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Shimizu E
Osaka City Univ.
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Shimizu E
Osaka City Univ. Osaka‐shi Jpn
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Zhang Yitong
Faculty of Engineering, Osaka City University
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Takahashi Hideya
Faculty of Engineering, Osaka City University
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Shigeta Kazuo
Faculty of Engineering, Osaka City University
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Zhang Yitong
Faculty Of Engineering Osaka City University
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Shigeta K
Osaka City Univ.
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Shigeta Kazuo
Faculty Of Engineering Osaka City University
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Shimizu Eiji
Faculty Of Engineering Osaka City University
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Takahashi H
Osaka City Univ.
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Takahashi Hideya
Department Of Electrical Engineering Osaka City University
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