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