离散记忆混沌图的设计:分数阶记忆、动力学和应用

Huihai Wang, Zuyi Xin, Shaobo He, Kehui Sun
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引用次数: 0

摘要

本文在卡普托差分的基础上推导出了离散混沌(DFM)模型,并设计了一种新的分数阶混沌图。通过Lyapunov指数谱、分岔图、PE复杂性和多稳定性分析,详细研究了所提出图的动力学特性。与耦合离散整数阶忆阻器(DIM)相比,与 DFM 耦合的图谱具有更丰富的动力学特性,包括更大的吸引子分布、更少的数值周期窗口和更高的复杂性。此外,阶数还成为额外的分岔参数。最后,在现场可编程门阵列(FPGA)平台上实现了所提出的映射,并将其应用于伪随机数发生器(PRNG)中,进一步证明了其应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a discrete memristive chaotic map: fractional-order memory, dynamics and application
In this paper, a discrete fracmemristor (DFM) model is derived based on the Caputo difference, and a new fractional-order chaotic map is designed. Dynamics of proposed map is investigated in detail by means of Lyapunov exponent spectra, bifurcation diagrams, PE complexity and multistability analyses. Compared with the coupled discrete integer-order memristor (DIM), the map coupled with the DFM products richer dynamics, including larger attractor distribution, less numerically periodic windows, and higher complexity. Besides, the order becomes additional bifurcation parameter. Finally, the proposed map is implemented on Field-Programmable Gate Array (FPGA) platform, and applied in a pseudorandom number generator (PRNG), which further demonstrate its application value.
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