Periodicity and synchronization of coupled memristive neural networks with supremums

This paper investigates the periodicity and synchronization of the coupled memristive neural networks with supremums and time-varying delays. By employing a novel ω-matrix measure approach and classical Filippov?s discontinuous theory, some new sufficient conditions are derived to ensure the global exponential periodicity and the stability of the memristive neural network. Furthermore, the synchronization condition for the drive-response memristive neural networks via the error-feedback control scheme is also derived. Finally, numerical examples are provided to demonstrate the validity of the main results. Author-HighlightsA general model of memristive neural network with supremums is proposed.Different from traditional Lyapunov method, a novel ω-matrix measure approach is adopted.Several simple but efficient criteria are derived for the periodicity and stability of the proposed model.The method is further applied to the synchronization control of drive-response neural networks.

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