Synchronization analysis for stochastic multi-layer networks: Event-based impulsive control with predefined impulsive intervals

This article explores the novel approach to addressing the intra/inter-layer synchronization challenges in stochastic multi-layer networks (SMLNs). First, considering the influence of time delay in control, an event-triggered delayed impulsive control (ETDIC) strategy is developed, where the impulsive instant is determined by the predesigned event-triggered mechanism. Moreover, by introducing piecewise auxiliary functions, it effectively excludes Zeno behavior within the ETDIC framework. The study then derives sufficient conditions for ensuring intra- and inter-layer; synchronization, leveraging the Lyapunov method and rigorous mathematical analysis. Finally, theoretical results are validated through numerical simulations.

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Publication Details

Journal
Nonlinear Analysis Modelling and Control
Published
2025-10-20
DOI
https://doi.org/10.15388/namc.2025.30.43839
Primary Topic
Neural Networks Stability and Synchronization
Type
article
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article

Synchronization analysis for stochastic multi-layer networks: Event-based impulsive control with predefined impulsive intervals

Cheng Hu, Jinling Wang, Jiarong Li, Haijun Jiang et al.
Nonlinear Analysis Modelling and Control
Neural Networks Stability and Synchronization
article

Synchronization analysis for stochastic multi-layer networks: Event-based impulsive control with predefined impulsive intervals

Cheng Hu, Jinling Wang, Jiarong Li, Haijun Jiang, Hengyu Liu
article en

Abstract

This article explores the novel approach to addressing the intra/inter-layer synchronization challenges in stochastic multi-layer networks (SMLNs). First, considering the influence of time delay in control, an event-triggered delayed impulsive control (ETDIC) strategy is developed, where the impulsive instant is determined by the predesigned event-triggered mechanism. Moreover, by introducing piecewise auxiliary functions, it effectively excludes Zeno behavior within the ETDIC framework. The study then derives sufficient conditions for ensuring intra- and inter-layer; synchronization, leveraging the Lyapunov method and rigorous mathematical analysis. Finally, theoretical results are validated through numerical simulations.

Nonlinear Analysis Modelling and ControlVol. 30(6)
Jimei University (CN), Yili Normal University (CN), Xinjiang University (CN)
Openalex Percentile: Top 65%
Neural Networks Stability and Synchronization
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Synchronization analysis for stochastic multi-layer networks: Event-based impulsive control with predefined impulsive intervals — Cheng Hu, Jinling Wang, et al. · Nonlinear Analysis Modelling and Control (2025) | TGRS Research Map | TGRS