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Fixed-time synchronization of coupled memristive neural networks via event-triggered control
Applied Mathematics and Computation ( IF 4 ) Pub Date : 2021-08-01 , DOI: 10.1016/j.amc.2021.126542
Yuangui Bao 1 , Yijun Zhang 1 , Baoyong Zhang 1
Affiliation  

This paper is concerned with the fixed-time synchronization of coupled memristive neural networks (MNNs). To reduce the frequency of controller update, an event-triggered control approach is introduced. For this synchronization problem, the main difficulty lies in how to launch the fixed-time analysis in the parameter unmatching conditions and with event-triggered schemes. For the case when each follower in coupled MNNs have direct access to the leader MNN, a decentralized event-triggered scheme is provided. A distributed event-triggered controller is also designed when the node in coupled MNNs can only get the information of its neighbors. Some sufficient criteria are derived to guarantee the fixed-time event-triggered synchronization of considered coupled MNNs under these two situations, respectively. The upper bounds of the settling time are given and the Zeno behaviour is excluded for the two cases. Two numerical examples are provided to show the effectiveness of the obtained results. A potential application in secure communication is further discussed.



中文翻译:

通过事件触发控制的耦合忆阻神经网络的固定时间同步

本文关注的是耦合忆阻神经网络 (MNN) 的固定时间同步。为了减少控制器更新的频率,引入了事件触发控制方法。对于这个同步问题,主要难点在于如何在参数不匹配的情况下和事件触发方案下进行定时分析。对于耦合 MNN 中的每个跟随者都可以直接访问领导者 MNN 的情况,提供了一个分散的事件触发方案。当耦合的 MNN 中的节点只能获取其邻居的信息时,还设计了分布式事件触发控制器。推导出了一些足够的标准来分别保证在这两种情况下所考虑的耦合 MNN 的固定时间事件触发同步。给出了稳定时间的上限,并且排除了两种情况下的 Zeno 行为。提供了两个数值例子来说明所得结果的有效性。进一步讨论了在安全通信中的潜在应用。

更新日期:2021-08-02
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