Abstract
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 Ito 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.
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