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Performance of Chaos and Burst Noises Injected to the Hopfield NN for Quadratic Assignment Problems
Yoko UWATE Yoshifumi NISHIO Tetsushi UETA Tohru KAWABE Tohru IKEGUCHI
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2004/04/01
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Neural Networks and Bioengineering
chaos, intermittency, burst noise, neural network, combinatorial optimization problems, QAP,
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In this paper, performance of chaos and burst noises injected to the Hopfield Neural Network for quadratic assignment problems is investigated. For the evaluation of the noises, two methods to appreciate finding a lot of nearly optimal solutions are proposed. By computer simulations, it is confirmed that the burst noise generated by the Gilbert model with a laminar part and a burst part achieved the good performance as the intermittency chaos noise near the three-periodic window.