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Dynamic characteristics in two-dimensional FitzHugh–Nagumo neural system driven by Lévy noise

In this paper, the steady state characteristics and stochastic resonance (SR) in two-dimensional FitzHugh–Nagumo (FHN) neuron system driven by Lévy noise are studied. The system is simulated by Janicki–Weron algorithm and fourth-order Runge–Kutta method, and the steady state characteristics of the system are analyzed by stationary probability density (SPD) functions. Then, the SR is determined by the classical measure of signal-to-noise ratio (SNR). Through numerical simulation, it is found that the Lévy noise can induce the transition of the system. In addition, the effects of different parameters on the SR are analyzed by SNR.