Stability of stochastic impulsive reaction-diffusion neural networks with S-type distributed delays and its application to image encryption

Tengda Wei, Ping Lin, Yangfan Wang (Lead / Corresponding author), Linshan Wang (Lead / Corresponding author)

Research output: Contribution to journalArticle

8 Citations (Scopus)
13 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)35-45
Number of pages11
JournalNeural Networks
Volume116
Early online date4 Apr 2019
DOIs
Publication statusPublished - Aug 2019

Keywords

  • Image encryption
  • Impulse
  • S-type distributed delay
  • Stochastic reaction–diffusion neural network

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