Fixed-time synchronization problem of coupled delayed discontinuous neural networks via indefinite derivative method
In this brief, we introduce a class of coupled delayed nonautonomous neural networks (CDNNs) with discontinuous activation function. Different from the conventional Lyapunov method, this brief uses the implementation of an indefinite derivative to deal with the nonautonomous system for the case that...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
AIMS Press
2023-01-01
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Series: | Electronic Research Archive |
Subjects: | |
Online Access: | https://www.aimspress.com/article/doi/10.3934/era.2023084?viewType=HTML |
Summary: | In this brief, we introduce a class of coupled delayed nonautonomous neural networks (CDNNs) with discontinuous activation function. Different from the conventional Lyapunov method, this brief uses the implementation of an indefinite derivative to deal with the nonautonomous system for the case that the topology between neurons is nonlinear coupling, and the system can achieve synchronization in fixed time by selecting the suitable control scheme. The settling time estimation of the system which can get rid of the dependence on the initial value is given. Finally, two examples are given to verify the correctness of the results in this paper. |
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ISSN: | 2688-1594 |