Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
Special Section on Bifurcations
Searching characteristics of chaotic neurodynamics for combinatorial optimization
Takafumi MatsuuraKazumiti NumataTohru Ikeguchi
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2012 Volume 3 Issue 4 Pages 573-585


An effective algorithm for solving combinatorial optimization problems by using chaotic neurodynamics has already been proposed. Although numerical simulations show that the algorithm is highly efficient, the reason behind its effectiveness has not yet been clarified. In this study, we investigated the searching characteristics of this algorithm for solving combinatorial optimization problems by employing the method of surrogate data, which is frequently used in the field of nonlinear time series analysis. We evaluated how solving abilities depend on bifurcation parameters related to the refractory effects in the chaotic neural networks. Then, we found that the considerable searching ability is decided by refractory effects after neuron firing.

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© 2012 The Institute of Electronics, Information and Communication Engineers
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