A Hierarchical Neural Network Model for Category Detection : General and Mathematical Physics
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概要
- 論文の詳細を見る
The present paper proposes a neural network model which has an ability of hierarchical categorization. The network is self-organized by a Hebbian learning rule and each cell in the network is differentiated to detect respectively a set of input signals which corresponds to a category. If mutual connections among the cells are suitable in strength and input signals have a hierarchical structure, a hierarchical relation emerges among the detector cells.
- 理論物理学刊行会の論文
- 1989-02-25
著者
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Sakaguchi Hidetsugu
Department Of Applied Physics Faculty Of Engineering Kyushu University
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SAKAGUCHI Hidetsugu
Department of Physics, College of General Education, Kyushu University
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SAKAGUCHI Hidetsugu
Department of Physics, Kyoto University
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SAKAGUCHI Hidetsugu
Department of Applied Sciences for Electronics and Materials Interdisciplinary Graduate School of Engineering Sciences Kyushu University
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