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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
Publication Date: 2004/04/01
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.