Mathematics (Mar 2023)

Mathematical and Experimental Model of Neuronal Oscillator Based on Memristor-Based Nonlinearity

  • Ivan Kipelkin,
  • Svetlana Gerasimova,
  • Davud Guseinov,
  • Dmitry Pavlov,
  • Vladislav Vorontsov,
  • Alexey Mikhaylov,
  • Victor Kazantsev

DOI
https://doi.org/10.3390/math11051268
Journal volume & issue
Vol. 11, no. 5
p. 1268

Abstract

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This article presents a mathematical and experimental model of a neuronal oscillator with memristor-based nonlinearity. The mathematical model describes the dynamics of an electronic circuit implementing the FitzHugh–Nagumo neuron model. A nonlinear component of this circuit is the Au/Zr/ZrO2(Y)/TiN/Ti memristive device. This device is fabricated on the oxidized silicon substrate using magnetron sputtering. The circuit with such nonlinearity is described by a three-dimensional ordinary differential equation system. The effect of the appearance of spontaneous self-oscillations is investigated. A bifurcation scenario based on supercritical Andronov–Hopf bifurcation is found. The dependence of the critical point on the system parameters, particularly on the size of the electrode area, is analyzed. The self-oscillating and excitable modes are experimentally demonstrated.

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