Markov Chain Modeling of Intermittency Chaos and Its Application to Hopfield NN

Yoko UWATE  Yoshifumi NISHIO  Akio USHIDA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E87-A   No.4   pp.774-779
Publication Date: 2004/04/01
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Selected Papers from the 16th Workshop on Circuits and Systems in Karuizawa)
intermittency chaos,  burst noise,  Markov chain,  neural network,  QAP,  associative memory,  

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In this study, a modeling method of the intermittency chaos using the Markov chain is proposed. The performances of the intermittency chaos and the Markov chain model are investigated when they are injected to the Hopfield Neural Network for a quadratic assignment problem or an associative memory. Computer simulated results show that the proposed modeling is good enough to gain similar performance of the intermittency chaos.