Journal
NEURAL NETWORKS
Volume 125, Issue -, Pages 174-184Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2020.02.008
Keywords
Fractional-order discrete systems; Neural networks; Synchronization; Image encryption
Funding
- National Natural Science Funds of China [61403115, 11571016, 11971032]
- Society Science Foundation from Ministry of Education of China [19YJCZH265]
- Fundamental Research Funds for the Central Universities, China [JZ2016HGXJ0022]
- Science and Technology Program of Guangzhou, China [201707010031]
- First Class Discipline of Zhejiang-A (Zhejiang Univeristy of Finance and Economics-Statistics)
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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. (c) 2020 Elsevier Ltd. All rights reserved.
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