Abstract This paper investigates the problem of event-based sliding-mode synchronization of memristive neural networks with delay through continuous/periodic sampling algorithm. Memristive neural networks are converted into the form of general neural networks by nonsmooth analysis. Then the controller is designed on the sliding surface selected and the trajectory of the system with this controller are analyzed in detail. Based on the continuous sampling, this paper further draws new results with the periodic sampling rule. Finally, some numerical examples are given to verify the correctness of the theoretical results.

中文翻译：

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通过连续/周期采样算法实现延迟忆阻神经网络的基于事件的滑模同步

摘要 本文通过连续/周期采样算法研究了具有延迟的忆阻神经网络的基于事件的滑模同步问题。忆阻神经网络通过非光滑分析转化为一般神经网络的形式。然后在选定的滑动面上设计控制器，并详细分析带有该控制器的系统的轨迹。本文在连续抽样的基础上，进一步利用周期性抽样规则得出新的结果。最后给出了一些数值算例来验证理论结果的正确性。