4.5 Article

Continuous non-autonomous memristive Rulkov model with extreme multistability*

期刊

CHINESE PHYSICS B
卷 30, 期 12, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.1088/1674-1056/ac2f30

关键词

extreme multistability; memristor; electromagnetic induction; Rulkov model

资金

  1. National Natural Science Foundation of China [12172066, 61801054, 51777016]
  2. Natural Science Foundation of Jiangsu Province, China [BK20160282]
  3. Postgraduate Research and Practice Innovation Program of Jiangsu Province, China [KYCX21 2823]

向作者/读者索取更多资源

This paper introduces a continuous non-autonomous memristive Rulkov model, which reveals extreme multistability by considering the effects of electromagnetic induction and external stimulus. Numerical simulations and hardware experiments are conducted to verify the extreme multistability, broadening the future engineering applications of the Rulkov model.
Based on the two-dimensional (2D) discrete Rulkov model that is used to describe neuron dynamics, this paper presents a continuous non-autonomous memristive Rulkov model. The effects of electromagnetic induction and external stimulus are simultaneously considered herein. The electromagnetic induction flow is imitated by the generated current from a flux-controlled memristor and the external stimulus is injected using a sinusoidal current. Thus, the presented model possesses a line equilibrium set evolving over the time. The equilibrium set and their stability distributions are numerically simulated and qualitatively analyzed. Afterwards, numerical simulations are executed to explore the dynamical behaviors associated to the electromagnetic induction, external stimulus, and initial conditions. Interestingly, the initial conditions dependent extreme multistability is elaborately disclosed in the continuous non-autonomous memristive Rulkov model. Furthermore, an analog circuit of the proposed model is implemented, upon which the hardware experiment is executed to verify the numerically simulated extreme multistability. The extreme multistability is numerically revealed and experimentally confirmed in this paper, which can widen the future engineering employment of the Rulkov model.

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