Abstract
In this paper, Fourier series chaotic neural network model is presented to improve the ability to escape the local minima so that it can effectively solve optimization problems. 10-city traveling salesman problem was given and the effects of the non-monotonous degree in the model on solving 10-city traveling salesman problem were discussed, the figures of the reversed bifurcation and the maximal Lyapunov exponents of single neural unit were given. The new model is applied to solve several function optimizations. Seen from the simulation results, the new model is powerful than the common chaotic neural network.
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Zhang, Jh., Sun, Cz., Xu, Yq. (2010). Fourier Series Chaotic Neural Networks. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13278-0_18
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DOI: https://doi.org/10.1007/978-3-642-13278-0_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13277-3
Online ISBN: 978-3-642-13278-0
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