Implementation of the Simple Hyperchaotic Memristor Circuit with Attractor Evolution and Large-Scale Parameter Permission.

Gang Yang, Xiaohong Zhang, Ata Jahangir Moshayedi
Author Information
  1. Gang Yang: School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China. ORCID
  2. Xiaohong Zhang: School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China. ORCID
  3. Ata Jahangir Moshayedi: School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China.

Abstract

A novel, simple, four-dimensional hyperchaotic memristor circuit consisting of two capacitors, an inductor and a magnetically controlled memristor is designed. Three parameters (, , ) are especially set as the research objects of the model through numerical simulation. It is found that the circuit not only exhibits a rich attractor evolution phenomenon, but also has large-scale parameter permission. At the same time, the spectral entropy complexity of the circuit is analyzed, and it is confirmed that the circuit contains a significant amount of dynamical behavior. By setting the internal parameters of the circuit to remain constant, a number of coexisting attractors are found under symmetric initial conditions. Then, the results of the attractor basin further confirm the coexisting attractor behavior and multiple stability. Finally, the simple memristor chaotic circuit is designed by the time-domain method with FPGA technology and the experimental results have the same phase trajectory as the numerical calculation results. Hyperchaos and broad parameter selection mean that the simple memristor model has more complex dynamic behavior, which can be widely used in the future, in areas such as secure communication, intelligent control and memory storage.

Keywords

References

  1. Nature. 2008 May 1;453(7191):80-3 [PMID: 18451858]
  2. Chaos. 2018 Jan;28(1):013125 [PMID: 29390635]
  3. Entropy (Basel). 2019 Jan 07;21(1): [PMID: 33266750]
  4. Entropy (Basel). 2021 Jun 05;23(6): [PMID: 34198759]

Grants

  1. 61763017, 51665019/National Natural Science Foundation of China

Word Cloud

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