4.7 Article

Multi-scroll hidden attractor in memristive HR neuron model under electromagnetic radiation and its applications

期刊

CHAOS
卷 31, 期 1, 页码 -

出版社

AIP Publishing
DOI: 10.1063/5.0035595

关键词

-

资金

  1. National Natural Science Foundation of China (NNSFC) [61876209]
  2. National Key Research and Development Program of China [2017YFC1501301]

向作者/读者索取更多资源

This study presents a novel non-equilibrium Hindmarsh-Rose neuron model with memristive electromagnetic radiation effect. Through numerical simulations and hardware experiments, it is demonstrated that this model exhibits complex dynamics and high security, making it suitable for real-world applications.
This paper aims to propose a novel no-equilibrium Hindmarsh-Rose (HR) neuron model with memristive electromagnetic radiation effect. Compared with other memristor-based HR neuron models, the uniqueness of this memristive HR neuron model is that it can generate multi-scroll hidden attractors with sophisticated topological structures and the parity of the scrolls can be controlled conveniently with changing the internal parameters of the memristor. In particular, the number of scrolls of the multi-scroll hidden attractors is also associated with the intensity of external electromagnetic radiation stimuli. The complex dynamics is numerically studied through phase portraits, bifurcation diagrams, Lyapunov exponents, and a two-parameter diagram. Furthermore, hardware circuit experiments are carried out to demonstrate theoretical analyses and numerical simulations. From the perspective of engineering application, a pseudo-random number generator is designed. Besides, an image encryption application and security analysis are also performed. The obtained results show that the memristive HR neuron model possesses excellent randomness and high security, which is suitable for chaos-based real-world applications. Published under license by AIP Publishing.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据