Stability Analysis of Stochastic Fuzzy Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms

摘要

This paper investigates the problem of the global exponential stability for a class of stochastic Takagi-Sugeno fuzzy neural networks (STSFNNs) with time-varying delays and reaction-diffusion terms. Based on the piecewise Lyapunov-Krasovskii functional, Poincare integral inequality, and ltd differential formula, we obtain some sufficient conditions ensuring the global exponential stability of an equilibrium point for STSFNNs with time-varying delays and reaction-diffusion terms. These sufficient conditions depend on the reaction-diffusion terms and time delays. Finally, some examples are given to show the effectiveness and superiority of the proposed approach.