Fixed-time synchronization of coupled memristive neural networks via event-triggered control

人工神经网络 同步(交流) 计算机科学 控制理论(社会学) 事件(粒子物理) 控制(管理) 数学 拓扑(电路) 人工智能 物理 组合数学 量子力学
作者
Yuangui Bao,Yijun Zhang,Baoyong Zhang
出处
期刊:Applied Mathematics and Computation [Elsevier]
卷期号:411: 126542-126542 被引量:16
标识
DOI:10.1016/j.amc.2021.126542
摘要

• The fixed-time synchronization problem to coupled memristive neural networks is solved. • A fixed-time analysis method is provided for the system with parameter unmatching condi- tions and event-triggered schemes. • The design methods for both decentralized and distributed event-triggered schemes are provided. • A potential application in secure communication is discussed. 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.

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