Exponential adaptive synchronization of stochastic memristive chaotic recurrent neural networks with time-varying delays

Abstract This paper is focused on the global exponential adaptive synchronization problem of two stochastic memristive chaotic neural networks with both stochastic disturbance and time-varying delays. First, in order to develop the guaranteed cost control, a periodically alternate adaptive rule is designed. Then, by constructing appropriate Lyapunov–Krasovskii functionals, several easily verified synchronization criteria are derived to guarantee exponential adaptive synchronization of drive-response stochastic memristive chaotic recurrent neural networks. Lastly, a numerical simulation is carried out to demonstrate the effectiveness of the proposed results.

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