Fourier Series Chaotic Neural Networks

被引：0

作者：

Xu, Yao-qun ^{[1
]}

He, Shao-ping ^{[1
]}

机构：

[1] Harbin Univ Commerce, Inst Syst Engn, Harbin 150028, Peoples R China

来源：

ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES | 2008年 / 15卷

关键词：

Chaotic neural network; Fourier series; Trigonometric function;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Chaotic neural networks have been proved to be strong tools to solve the optimization problems. In order to escape the local minima, a new chaotic neural network model called Fourier series chaotic neural network was presented. The activation function of the new model is non-monotonous, which is composed of sigmoid and trigonometric function. First, the figures of the reversed bifurcation and the maximal Lyapunov exponents of single neural unit were given. Second, the new model is applied to solve several function optimizations. Finally, 10-city traveling salesman problem is given and the effects of the non-monotonous degree in the model on solving 10-city traveling salesman problem are discussed. Seen from the simulation results, the new model we proposed is more effective.

引用

页码：84 / 91

页数：8

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