For EDITORS

For READERS

All Issues

Vol.14, 2024
Vol.10, 2020
Vol.9, 2019
Vol.8, 2018
Vol.7, 2017
Vol.6, 2016
Vol.5, 2015
Vol.4, 2014
Vol.3, 2013
Vol.2, 2012
Vol.1, 2011
Volume 14, Number 4, 2024, Pages -                                                                DOI:10.11948/JAAC-2022-0300
Fixed-time synchronization of a reaction-diffusion BAM neural network with distributed delay and its application to image encryption
Jiazhe Lin,Ling Zhou,Zhu Zhou
Keywords:BAM neural network, fixed-time synchronization, image encryption, reaction-diffusion, distributed delay
Abstract:
      In this paper, the fixed-time synchronization of reaction-diffusion BAM neural networks is investigated, where both discrete and distributed delays are taken into account. Combining Lyapunov stability theory and several integral inequalities, fixed-time synchronization criteria are established. Through sensitivity analysis, we find the key controller parameters that have a great influence on the maximum settling time. Using the chaotic sequences generated by the neural network, the color image can be encrypted by the Arnold Cat Map and the pixel diffusion. Experiments show that the image encryption algorithm designed in this paper has good properties of security and anti-attacking, which meets the requirements for the secure transmission of image information.
PDF      Download reader