Neuromorphic Oscillators and Electronic Implementation of One Novel MFNN Model

Abstract

Exploring the equivalent mathematical and physical representation of biological neurons is one of the most essential tasks for building the complex neural systems and networks. In this paper, we focus on constructing a novel memristive FitzHugh-Nagumo Neuron (MFNN) model to simulate the nonlinear oscillation behaviors and neuromorphic dynamics of some biological neurons. Then, the relationship between ranges of circuit parameter values and pinched hysteresis loop are presented. Moreover, its behaviors and neuromorphic nonlinear dynamics are analyzed and several essential curves are depicted, such as phase portraits, time-domain waveforms, Lyapunov exponent spectrums, Poincare maps, the bifurcation diagrams, and so on. Furthermore, the most important characteristics are the generation of memristive oscillators and bursting firing phenomenon. There is no doubt that the good agreement among theoretical analysis, simulation and experimental results verifies the practicability and flexibility of the configured MFNN model.