DocumentCode :
2347556
Title :
On Chaos Character of Dynamic Fuzzy Neural Network
Author :
Tang, Mo ; Wang, Kejun ; Bi, Xiaojun
Author_Institution :
Dept. of Autom., Harbin Eng. Univ., Harbin, China
fYear :
2011
fDate :
15-19 April 2011
Firstpage :
1011
Lastpage :
1015
Abstract :
The chaos character of dynamic fuzzy neural network is further explored and analyzed in this paper applying the traditional Lyapunov exponent method. Firstly, the working principle of dynamic fuzzy neural network is introduced, and then the discretization network model is given by Euler method. The dissipation and chaos traits of single dynamic fuzzy neuron and dynamic fuzzy neural networks are proved separately. According to Lyapunov exponent discriminance criterion, four conditions are deduced, which the parameters should satisfy to prove the existence of chaos in single dynamic neuron and dynamic fuzzy neural network.
Keywords :
Lyapunov methods; fuzzy neural nets; Euler method; Lyapunov exponent discriminance criterion; chaos character; discretization network model; dynamic fuzzy neural network; single dynamic fuzzy neuron; Artificial neural networks; Chaos; Fuzzy control; Fuzzy neural networks; Neurons; Nonlinear dynamical systems; Power system dynamics; Lyapunov exponent; chaos; dynamic fuzzy neruon; dynamic fuzzy neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location :
Yunnan
Print_ISBN :
978-1-4244-9712-6
Electronic_ISBN :
978-0-7695-4335-2
Type :
conf
DOI :
10.1109/CSO.2011.183
Filename :
5957828
Link To Document :
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