Switching dynamics of a non-autonomous FitzHugh-Nagumo circuit with piecewise-linear flux-controlled memristor

Fuhong Min, Wen Zhang, Ziyi Ji and Lei Zhang

Chaos, Solitons & Fractals, 2021, vol. 152, issue C

Abstract: Memristor, as a nonlinear electronic component, has good switching characteristics, which makes it has excellent application in the field of artificial intelligence. The study for discontinuous dynamics of memristor-based neural network can best reflect the boundary effect of memristors and the complex nonlinear behaviors of system. In this paper, the non-autonomous FitzHugh-Nagumo neuronal circuit with piecewise memristor is investigated in flux-charge domain through the theory of switching flow. The sufficient and necessary conditions of switching motions, such as passable and grazing on the boundary, are developed to understand the switching mechanism. The switching bifurcation diagrams with changing the system parameters and initial conditions are studied to reveal the hidden extreme multistability and coexisting attractors. The parameter mappings and basins of attractor are also carried out to express the coexistences of periodic orbits and chaos with different mapping structures. The simulation results show that the switching and grazing motion are verified the effectiveness the analysis conditions.

Keywords: FitzHugh-Nagumo circuit; Switching motion; Coexisting attractors; Mulitistability (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921007232

DOI: 10.1016/j.chaos.2021.111369

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