Quasisynchronization of Heterogeneous Neural Networks With Time-Varying Delays via Event-Triggered Impulsive Controls

Wed Sun, Zixin Yuan,Zhenyu Lu,Junhao Hu,Shihua Chen

IEEE Transactions on Cybernetics(2022)

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摘要
Time delays are unavoidable since they are ubiquitous and may have a great impact on the performance of neural networks. Resources efficiency is a common concern in many networked systems with limited resources. This article investigates quasisynchronization of the heterogeneous neural networks with time-varying delays via event-triggered impulsive controls which combine the impulsive control and the event-triggered technique. The centralized and distributed event-triggered impulsive controls are, respectively, presented. The suitable Lyapunov functions are constructed, and the triggering functions are derived, which guarantee that not only are the synchronization errors less than a non-negative bound but also the Zeno behaviors can be eliminated. It is suggested that the distributed one has great superiority in taking up fewer resources compared with the time-triggered impulsive control. Numerical examples are proposed to verify the validity of the centralized and distributed control methods.
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Neural Networks, Computer,Time Factors
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