Exponential synchronization of reaction-diffusion neural networks via asynchronous sampled-data event-triggered control

Pingge Chen; Haibo Zeng; Chenjie Xu; Pingge Chen; Haibo Zeng; Chenjie Xu

doi:10.3934/era.2026313

Electronic Research Archive

2026, Volume 34, Issue 10: 7244-7260. doi: 10.3934/era.2026313

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Theory article

Exponential synchronization of reaction-diffusion neural networks via asynchronous sampled-data event-triggered control

College of Science, Hunan University of Technology, Zhuzhou 412007, China

Received: 09 July 2026 Revised: 02 August 2026 Accepted: 06 August 2026 Published: 19 August 2026

This paper investigated the exponential synchronization (ES) problem of reaction-diffusion neural networks over directed networks under an asynchronous sampled-data event-triggered intermittent control scheme. By integrating event-triggered communication and intermittent control mechanisms, hybrid control framework was developed to reduce communication transmissions and control activation time. A Lyapunov–Krasovskii functional (LKF) involving historical-state integral terms was constructed, and sufficient synchronization conditions were derived using graph-theoretic techniques and inequality methods. The proposed criterion guaranteed exponential convergence of synchronization errors and avoided Zeno behavior. Numerical simulations demonstrated that the proposed strategy achieved satisfactory synchronization performance with reduced communication requirements.
- reaction-diffusion neural networks,
- exponential synchronization,
- sampled-data control,
- intermittent control,
- event-triggered control,
- directed networks
Citation: Pingge Chen, Haibo Zeng, Chenjie Xu. Exponential synchronization of reaction-diffusion neural networks via asynchronous sampled-data event-triggered control[J]. Electronic Research Archive, 2026, 34(10): 7244-7260. doi: 10.3934/era.2026313

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Abstract

This paper investigated the exponential synchronization (ES) problem of reaction-diffusion neural networks over directed networks under an asynchronous sampled-data event-triggered intermittent control scheme. By integrating event-triggered communication and intermittent control mechanisms, hybrid control framework was developed to reduce communication transmissions and control activation time. A Lyapunov–Krasovskii functional (LKF) involving historical-state integral terms was constructed, and sufficient synchronization conditions were derived using graph-theoretic techniques and inequality methods. The proposed criterion guaranteed exponential convergence of synchronization errors and avoided Zeno behavior. Numerical simulations demonstrated that the proposed strategy achieved satisfactory synchronization performance with reduced communication requirements.

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