New global exponential synchronization conditions for impulsive chaotic neural networks with multiple time-varying leakage and transmission delays: Applications for secure communications

Guangxun Chen, Yantao Wang and Xian Zhang

Chaos, Solitons & Fractals, 2025, vol. 191, issue C

Abstract: The problem of global exponential synchronization for impulsive chaotic neural networks with multiple time-varying transmission and leakage delays is studied in this article. A system solution-based direct analysis method is proposed to obtain sufficient conditions for global exponential synchronization of master–slave systems. On the one hand, the method is convenient for handling synchronization problems involving multiple time-varying delays. On the other hand, this method does not require the establishment of Lyapunov–Krasovskii functional, which results in a significant reduction in computations and simplicity of the proof process. Based on the synchronization results, a secure communication method is proposed. In the end, three numerical examples and an application show that the proposed synchronization and secure communication methods are effective. Significantly, this article is the first to deal with the synchronization problem of impulsive chaotic neural networks with multiple time-varying leakage and transmission delays.

Keywords: Chaotic neural networks; Impulse; Global exponential synchronization; Multiple time-varying transmission delays; Multiple time-varying leakage delays (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:191:y:2025:i:c:s0960077924013948

DOI: 10.1016/j.chaos.2024.115842

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