作者
Haruhiko Nishimura, Naofumi Katada, Kazuyuki Aihara
发表日期
2000/8
期刊
Neural Processing Letters
卷号
12
页码范围
49-58
出版商
Kluwer Academic Publishers
简介
We set up a signal-driven scheme of the chaotic neural network with the coupling constants corresponding to certain information, and investigate the stochastic resonance-like effects under its deterministic dynamics, comparing with the conventional case of Hopfield network with stochastic noise. It is shown that the chaotic neural network can enhance weak subthreshold signals and have higher coherence abilities between stimulus and response than those attained by the conventional stochastic model.
引用总数
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学术搜索中的文章
H Nishimura, N Katada, K Aihara - Neural Processing Letters, 2000