"Deterministic Diffusion" in a Neural Network Model (Special Section of Letters Selected from the 1994 IEICE Spring Conference)
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概要
- 論文の詳細を見る
This paper describes that a neural network, which consists of neurons with piecewise-linear sigmoid characteristics, is able to approximate any piecewise-linear map with origin symmetry. The neural network can generate "deterministic diffusion" originating from its diffusive trajectory.
- 社団法人電子情報通信学会の論文
- 1994-11-25
著者
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Uchiyama Akihiko
School of Sci. & Eng. Dept. of Elec. & Comm. Waseda Univ.
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Matsuda Hideo
Department Of Rehabilitation Engineering The Polytechnic University
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Matsuda Hideo
Department Of Chemistry Gunma University
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Matsuda Hideo
Department Of Bioinformatic Engineering Graduate School Of Information Science And Technology Osaka
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Uchiyama Akihiko
School of Science and Engineering, Waseda University
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