This paper investigates the exponential synchronization issue of stochastic delayed memristive neural networks (SDMNNs) via a novel hybrid control (HC), where impulsive instants are determined by the state-dependent trigger condition. The switching and quantification strategies are applied to the event-based impulsive controller to cope with the challenges induced concurrently by interval parameters, impulses, stochastic disturbance and time-varying delays. Furthermore, the control costs can be reduced and communication channels and bandwidths can be saved by using this designed controller. Then, novel Lyapunov functions and new analytical methods are constructed, which can be used to realize the exponential synchronization of SDMNNs via HC. Finally, a numerical simulation is provided to demonstrate our theoretical results.

本文研究了通过新型混合控制（HC）的随机延迟忆阻神经网络（SDMNN）的指数同步问题，其中冲动瞬间由状态相关的触发条件决定。切换和量化策略被应用于基于事件的脉冲控制器，以应对由间隔参数，脉冲，随机干扰和时变延迟同时引起的挑战。此外，通过使用这种设计的控制器，可以降低控制成本，并可以节省通信通道和带宽。然后，构造了新颖的李雅普诺夫函数和新的解析方法，可用于通过HC实现SDMNN的指数同步。最后，提供了一个数值模拟来证明我们的理论结果。