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Updated: Jan 26, 2026

Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Stability of stochastic impulsive reaction-diffusion neural networks with S-type distributed delays and its
Tengda Wei1, Ping Lin2, Yangfan Wang3
1School of Mathematical Sciences, Ocean University of China, Qingdao 266100, China; Department of Mathematics, University of Dundee, Dundee DD1 4HN, Scotland, United Kingdom.
Abstract:
In this paper, we study stochastic impulsive reaction-diffusion neural networks with S-type distributed delays, aiming to obtain the sufficient conditions for global exponential stability. First, an impulsive inequality involving infinite delay is introduced and the asymptotic behaviour of its solution is investigated by the truncation method. Then, global exponential stability in the mean-square sense of the stochastic impulsive reaction-diffusion system is studied by constructing a simple Lyapunov-Krasovskii functional where the S-type distributed delay is handled by the impulsive inequality. Numerical examples are also given to verify the effectiveness of the proposed results. Finally, the obtained theoretical results are successfully applied to an image encryption scheme based on bit-level permutation and the stochastic neural networks.
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