Synchronization of nonlinear neural networks with hybrid couplings and uncertain time-varying perturbations: A novel distributed-delay impulsive comparison principle
This paper investigates the synchronization of nonlinear drive-response neural networks subject to uncertain time-varying perturbations, non-delayed coupling, and distributed delay coupling. To address the influence of distributed and discrete delays on the system, we establish a novel impulsive com...
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| Published in | Neurocomputing (Amsterdam) Vol. 613; p. 128729 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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14.01.2025
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| Abstract | This paper investigates the synchronization of nonlinear drive-response neural networks subject to uncertain time-varying perturbations, non-delayed coupling, and distributed delay coupling. To address the influence of distributed and discrete delays on the system, we establish a novel impulsive comparison principle, extending the Halanay inequality. By leveraging Lyapunov stability theory, we derive sufficient conditions for the exponential synchronization of the neural networks using a delayed impulsive controller with historical status information. This approach relaxes the conventional constraint that impulsive delays must be smaller than impulsive intervals, thereby generalizing existing synchronization results for distributed delay networks. Numerical simulations for chaotic neural networks validate the theoretical results and demonstrate the sensitivity of the control gain matrix. |
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| AbstractList | This paper investigates the synchronization of nonlinear drive-response neural networks subject to uncertain time-varying perturbations, non-delayed coupling, and distributed delay coupling. To address the influence of distributed and discrete delays on the system, we establish a novel impulsive comparison principle, extending the Halanay inequality. By leveraging Lyapunov stability theory, we derive sufficient conditions for the exponential synchronization of the neural networks using a delayed impulsive controller with historical status information. This approach relaxes the conventional constraint that impulsive delays must be smaller than impulsive intervals, thereby generalizing existing synchronization results for distributed delay networks. Numerical simulations for chaotic neural networks validate the theoretical results and demonstrate the sensitivity of the control gain matrix. |
| ArticleNumber | 128729 |
| Author | Zhao, Yi Shi, Kaibo Fan, Hongguang |
| Author_xml | – sequence: 1 givenname: Hongguang orcidid: 0000-0003-0728-3042 surname: Fan fullname: Fan, Hongguang organization: College of Computer, Chengdu University, Chengdu 610106, China – sequence: 2 givenname: Kaibo surname: Shi fullname: Shi, Kaibo organization: School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu 610106, China – sequence: 3 givenname: Yi orcidid: 0000-0002-1765-8787 surname: Zhao fullname: Zhao, Yi email: yzhao@szu.edu.cn organization: School of Mathematical Sciences, Shenzhen University, Shenzhen 518060, China |
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| SubjectTerms | Complex network Distributed delay Impulsive interval Impulsive synchronization Uncertain perturbation |
| Title | Synchronization of nonlinear neural networks with hybrid couplings and uncertain time-varying perturbations: A novel distributed-delay impulsive comparison principle |
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