Adaptive synchronization of memristive neural networks with time-varying delays and reaction-diffusion term

This paper focuses on the synchronization control methodology for a class of delayed reaction–diffusion memristor-based neural networks. Adaptive controllers are designed such that the considered model can realize asymptotical and exponential synchronization goal under the framework of inequality techniques and Lyapunov method. The results obtained in this paper consider the effect of time delays as well as the reaction–diffusion terms, which generalize and improve some existing results. The derived synchronization criteria are presented in the form of algebraic, which can be easily verified. Finally, numerical example and its simulations are given to show the correctness of the obtained results.

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