Exponential synchronization of stochastic fuzzy cellular neural networks with time delay in the leakage term and reaction–diffusion

Separate studies have been published on the stability of fuzzy cellular neural networks with time delay in the leakage term and synchronization issue of coupled chaotic neural networks with stochastic perturbation and reaction–diffusion effects. However, there have not been studies that integrate the two fields. Motivated by the achievements from both fields, this paper considers the exponential synchronization problem of coupled chaotic fuzzy cellular neural networks with stochastic noise perturbation, time delay in the leakage term and reaction–diffusion effects using linear feedback control. Lyapunov stability theory combining with stochastic analysis approaches are employed to derive sufficient criteria ensuring the coupled chaotic fuzzy neural networks to be exponentially synchronized. This paper also presents an illustrative example and uses simulated results of this example to show the feasibility and effectiveness of the proposed scheme.

► We explore the issues of integrating leakage delay into the study of synchronization for fuzzy cellular neural networks. ► Linear feedback controller to guarantee the exponential synchronization for fuzzy cellular neural networks is obtained. ► Numerical simulations are carried out to demonstrate the effectiveness of the main results.