Stochastic resonance in a piecewise nonlinear model driven by multiplicative non-Gaussian noise and additive white noise

•The phenomenon of stochastic resonance in a piecewise nonlinear model is studied.•Model driven by multiplicative non-Gaussian noise and additive white noise.•The analytical expression of the signal-to-noise ratio (SNR) is derived.•The effect of noises, periodic signal and system parameters on SNR is discussed.•It is found that conventional stochastic resonance exists in this system.

The phenomenon of stochastic resonance (SR) in a piecewise nonlinear model driven by a periodic signal and correlated noises for the cases of a multiplicative non-Gaussian noise and an additive Gaussian white noise is investigated. Applying the path integral approach, the unified colored noise approximation and the two-state model theory, the analytical expression of the signal-to-noise ratio (SNR) is derived. It is found that conventional stochastic resonance exists in this system. From numerical computations we obtain that: (i) As a function of the non-Gaussian noise intensity, the SNR is increased when the non-Gaussian noise deviation parameter q is increased. (ii) As a function of the Gaussian noise intensity, the SNR is decreased when q is increased. This demonstrates that the effect of the non-Gaussian noise on SNR is different from that of the Gaussian noise in this system. Moreover, we further discuss the effect of the correlation time of the non-Gaussian noise, cross-correlation strength, the amplitude and frequency of the periodic signal on SR.