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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Bibliographic Details
Published inNeurocomputing (Amsterdam) Vol. 613; p. 128729
Main Authors Fan, Hongguang, Shi, Kaibo, Zhao, Yi
Format Journal Article
LanguageEnglish
Published Elsevier B.V 14.01.2025
Subjects
Complex network
Distributed delay
Impulsive interval
Impulsive synchronization
Uncertain perturbation
Impulsive interval
Impulsive synchronization
Uncertain perturbation
Complex network
Distributed delay
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Summary: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.
ISSN:0925-2312
DOI:10.1016/j.neucom.2024.128729