Observer-Based Synchronization and Quasi-Synchronization for Multiple Neural Networks with Time-Varying Delays

Biwen Li, Donglun Wang, Jingjing Huang and Miaomiao Wang

Complexity, 2022, vol. 2022, 1-15

Abstract: In this paper, we study the synchronization of a class of multiple neural networks (MNNs) with delay and directed disconnected switching topology based on state observer via impulsive coupling control. The coupling topology is connected sequentially, and the controller adjusts the state value through event-triggering strategies. Different from the related works on MNNs, its state in this paper is assumed to be unmeasurable, and the time delay is also unmeasurable. Therefore, the observer does not contain the time-delay term. The impulsive switching controller and observer controller adjust the system through the observed value. By constructing the corresponding augmented matrix, the system can finally achieve quasi-synchronization (synchronization). Through derivation, we give the sufficient conditions ensuring quasi-synchronization (synchronization) via the event-triggered impulse control mechanism. In addition, numerical simulation examples are given to test our results of the theorem.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:4038598

DOI: 10.1155/2022/4038598

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