Switching synchronization of reaction-diffusion neural networks with time-varying delays

Dandan Hu, Jieqing Tan, Kaibo Shi and Kui Ding

Chaos, Solitons & Fractals, 2022, vol. 155, issue C

Abstract: This paper explores the switching synchronization problem of reaction-diffusion neural networks with time-varying delays, and two improved synchronization switching law strategies are proposed for stability analysis. One is constructed by adopting a Lyapunov-Krasovskii functional combined with the use of improved Wirtinger's integral inequality for managing the reaction-diffusion terms. The other is designed to utilize the Lyapunov-Razumikhin function, which is easier to deal with the reaction-diffusion terms directly compared to the former one. As a result, the time-space feature of the proposed switching synchronization is more robust and compatible than previous works. Finally, the simulated numerical experiments make out the effectiveness of the developed approaches in this work.

Keywords: Switching reaction–diffusion neural networks; Synchronization; Switching-time-dependent Lyapunov functional/function; Switching law strategies; Time-varying delays (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:155:y:2022:i:c:s0960077921011206

DOI: 10.1016/j.chaos.2021.111766

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