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Dynamic associative memory using chaotic neural networks

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2 Author(s)
Fukuhara, Y. ; Graduate Sch. of Media & Gov., Keio Univ., Kanagawa, Japan ; Takefuji, Y.

In this paper, we propose a multimodule chaotic associative memory (MCAM) that uses chaotic neural networks. In this method, the chaotic associative memories are connected to each other. If MCAM can not obtain enough information of a target, MCAM shows a behavior that looks like human “perplexity”, where MCAM succeeds in one-to-many associations. And when MCAM obtains enough information to recognize a target, MCAM converges to a stable state. Although the structure of MCAM is simple, MCAM realizes one-to-many association by using chaotic dynamics

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Intelligent Processing and Manufacturing of Materials, 1999. IPMM '99. Proceedings of the Second International Conference on  (Volume:2 )

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