Statistical complexity and stochastic resonance in bistable coupled network systems excited by non-Gaussian noise

Abstract This study investigates stochastic resonance (SR) phenomena in bistable coupled networks driven by non-Gaussian noise. Employing signal-to-noise ratio (SNR) and statistical complexity as quantitative metrics, we characterize the SR behavior. First, the dimensionality of a coupled network system is reduced via the mean field theory. Subsequently, we derive closed-form analytical expressions of SNR by the path integral method, the slaving principle and the two-state model theory. Numerical simulations are used to validate the consistency between SR features identified through statistical complexity and those obtained via SNR calculations, thereby corroborating the reliability of our analytical framework. Both theoretical and numerical results conclusively demonstrate the occurrence of SR in the network system. Parametric analyses further elucidate the modulation of SR characteristics by three critical factors: non-Gaussian noise intensity parameters, noise correlation timescale and inter-node coupling strength. Finally, we explore the system’s size resonance properties.