Title :
Activation Function of Wavelet Chaotic Neural Networks
Author :
Yao-qun Xu ; Sun, Ming ; Guo, Meng-shu
Author_Institution :
Inst. of Comput. & Inf. Eng., Harbin Univ. of Commerce
Abstract :
In this paper, we studied the activation function of chaotic neural network, at first we review Chen´s chaotic neural network and then propose a novel chaotic neural network model whose activation function is compose of sigmoid and wavelet function. Second, we make an analysis of the largest Lyapunov exponents and the reversed bifurcations of the neural units of Chen´s and the proposed model. Third, 10-city traveling salesman problem (TSP) is given to make a comparison between them. Finally we conclude that the novel chaotic neural network model we propose is more valid
Keywords :
Lyapunov methods; bifurcation; neural nets; transfer functions; travelling salesman problems; wavelet transforms; Lyapunov exponents; activation function; chaotic neural networks; sigmoid function; traveling salesman problem; wavelet function; Bifurcation; Chaos; Computer networks; Continuous wavelet transforms; Control theory; Damping; Neural networks; Neurons; Sun; Traveling salesman problems; Chaotic neural network; activation function; the largest Lyapunov exponents; wavelet function;
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
DOI :
10.1109/COGINF.2006.365577