This paper is concerned with the complete synchronization of memristive neural networks (MNNs) with time-varying delays. An event-triggered hybrid state feedback and impulsive controller is designed to save the limited system communication resources, and parameter mismatch is considered in the control design process. Based on the Lyapunov functional approach and the comparison principle for impulsive systems, a sufficient synchronization criterion is developed to derive the master MNN and response MNN. Additionally, under the event-triggered mechanism there exists a positive lower bound for inter-execution time, which implies the avoidance of Zeno behavior. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed synchronization design methods.

本文涉及具有时变时滞的忆阻神经网络（MNN）的完全同步。设计了事件触发的混合状态反馈和脉冲控制器，以节省有限的系统通信资源，并且在控制设计过程中考虑了参数不匹配的问题。基于Lyapunov函数方法和脉冲系统的比较原理，提出了足够的同步准则来导出主MNN和响应MNN。此外，在事件触发机制下，执行时间之间存在一个正的下限，这意味着避免了芝诺行为。最后，提供了一个数值示例来证明所提出的同步设计方法的有效性。