On Chaos Character of Dynamic Fuzzy Neural Network

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.