Sequence Processing Neural Network with Q-States Monotonic Transfer Function
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概要
- 論文の詳細を見る
Storage capacity as for retrieval of sequences of binary patterns is investigated for a fully connected neural network with Q (>2)-states. By using a generating-function method of path-integral representation, we find that the network with Q-states monotonic transfer function retrieves more sequences of the stored patterns than that with a binary monotonic transfer function at zero temperature, if the control parameter is chosen optimally. We compare the results obtained by the analytic method with those by numerical simulations.
- 理論物理学刊行会の論文
- 2005-04-30
著者
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堀口 剛
東北大学大学院情報科学研究科情報基礎科学専攻
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HORIGUCHI Tsuyoshi
Department of Computer and Mathematical Sciences, Graduate School of Information Sciences, Tohoku Un
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Horiguchi Takayoshi
Deoartment Of Clinical Radiology Hiroshima International University
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Horiguchi Tsuyoshi
Tohoku Univ. Sendai
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KATAYAMA Katsuki
Department of Computer Science and Systems Engineering, Muroran Institute of Technology
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Katayama Katsuki
Department Of Computer And Mathematical Sciences Graduate School Of Information Sciences Tohoku Univ
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Katayama Katsuki
Department Of Computer Science And Systems Engineering Muroran Institute Of Technology
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Horiguchi Tsuyoshi
Department Of Applied Science Faculty Of Engineering Tohoku University
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