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.