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Fixed-Time Synchronization of Complex-Valued Memristor-Based Neural Networks with Impulsive Effects

机译：基于复合忆因器的神经网络具有脉冲效应的定时同步

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摘要

In this paper, the fixed-time synchronization of complex-valued memristor-based neural networks with impulsive effects is investigated. We first separate these complex-valued networks into real and imaginary parts, and design the appropriate controllers. Then apply the set-valued map and the differential inclusion theorem to handle the discontinuity problems at the right-hand side of the drive-response systems. By constructing the comparison systems together with the Lyapunov function, we get the fixed-time synchronization conditions. Moreover, the estimate of the settling time is also explicitly obtained. Finally, two examples and their numerical simulations are presented to show the effectiveness of the obtained theoretical results.
机译：本文研究了复方基于映射器的神经网络的定时同步，具有脉冲效应。我们首先将这些复合值的网络分为真实和虚部，并设计适当的控制器。然后应用设定值的地图和差分夹杂物定理以处理驱动响应系统右侧的不连续问题。通过将比较系统与Lyapunov函数一起构建，我们得到了固定时间同步条件。此外，还明确获得了沉降时间的估计。最后，提出了两个例子及其数值模拟以显示所获得的理论结果的有效性。

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