School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China.
Texas A & M University at Qatar, PO Box 23874, Doha, Qatar.
Neural Netw. 2020 May;125:174-184. doi: 10.1016/j.neunet.2020.02.008. Epub 2020 Feb 22.
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.
本文提出了左 Caputo 离散δ意义下的三维分数阶(FO)离散型 Hopfield 神经网络(FODHNN),研究了 FODHNN 的动态行为和同步,并将系统应用于图像加密。首先,FODHNN 表现出丰富的非线性动力学行为。通过相图、分岔图和 Lyapunov 指数验证了该系统中的混沌动力学。此外,通过 FO 离散线性系统的稳定性定理,设计了一个合适的控制方案,实现了 FODHNN 的同步。最后,提出了基于混沌 FODHNN 的图像加密系统。给出了一些安全性分析和测试,以证明加密系统的有效性。