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

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.

Automated summary

This article introduces 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. The nonlinear component of the circuit is the Au/Zr/ZrO2(Y)/TiN/Ti memristive device. This device is fabricated on an oxidized silicon substrate using magnetron sputtering. The circuit with this nonlinearity is described by a three-dimensional ordinary differential equation system. The article explores the effect of spontaneous self-oscillations, identifies a bifurcation scenario based on supercritical Andronov-Hopf bifurcation, and analyzes the dependence of the critical point on system parameters, particularly the size of the electrode area. Experimental demonstrations of self-oscillating and excitable modes are provided.