Chaos in fractional-order discrete neural networks with application to image encryption.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date: Feb 22, 2020

Abstract

In this paper, a three-dimensional fractional-order (FO) discrete Hopfield neural network (FODHNN) in the left Caputo discrete delta's sense is proposed, the dynamic behavior and synchronization of FODHNN are studied, and the system is applied to image encryption. First, FODHNN is shown to exhibit rich nonlinear dynamics behaviors. Phase portraits, bifurcation diagrams and Lyapunov exponents are carried out to verify chaotic dynamics in this system. Moreover, by using stability theorem of FO discrete linear systems, a suitable control scheme is designed to achieve synchronization of the FODHNN. Finally, image encryption system based on the chaotic FODHNN is presented. Some security analysis and tests are given to show the effective of the encryption system.

Authors

  • Liping Chen
    Department of Gastroenterology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Hao Yin
    CAS Key Laboratory of Tropical Marine Bio-resources and Ecology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China.
  • Tingwen Huang
  • Liguo Yuan
    College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, China.
  • Song Zheng
    Department of Mathematics, School of Data Science, Zhejiang University of Finance and Economics, Hangzhou, 310018, China. Electronic address: szh070318@zufe.edu.cn.
  • Lisheng Yin
    School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China.

Keywords

External Resources

Popular Topics
Recent Journals