Multiplexing-based control of stochastic resonance

Abstract

We show that multiplexing allows to control noise-induced dynamics of multilayer networks in the regime of stochastic resonance. We illustrate this effect on an example of two- and multi-layer networks of bistable overdamped oscillators. In particular, we demonstrate that multiplexing suppresses the effect of stochastic resonance, if the periodic forcing is present in only one layer. In contrast, the multiplexing allows to enhance the stochastic resonance, if the periodic forcing and noise are present in all the interacting layers. In such a case the impact of multiplexing has a resonant character: the most pronounced effect of stochastic resonance is achieved for an appropriate intermediate value of coupling strength between the layers. Moreover, multiplexing-induced enhancement of the stochastic resonance can become more pronounced for increasing number of coupled layers. To visualize the revealed phenomena, we use the evolution of the dependence of the signal-to-noise ratio on the noise intensity for varying strength of coupling between the layers.

arXiv comment7 pages, 4 figures

References in corpus (16)

• Stochastic resonance and noise delayed extinction in a model of two competing species
• Dynamics of Random Neural Networks with Bistable Units
• Frequency and Phase Synchronization in Stochastic Systems
• Delayed-feedback chimera states: Forced multiclusters and stochastic resonance
• Weak multiplexing in neural networks: Switching between chimera and solitary states
• Stochastic gain in population dynamics
• Coherence resonance in a network of FitzHugh-Nagumo systems: interplay of noise, time-delay and topology
• Understanding and mitigating noise in trained deep neural networks
• Control of coherence resonance by self-induced stochastic resonance in a multiplex neural network
• Stochastic Resonance in Spatially Extended Systems: The Role of Far from Equilibrium Potentials
• Fundamental aspects of noise in analog-hardware neural networks
• Control of coherence resonance in multiplex neural networks
• Solitary states in multiplex neural networks: onset and vulnerability
• A bio-inspired bistable recurrent cell allows for long-lasting memory
• Asymmetry-induced order in multilayer networks
• Noise mitigation strategies in physical feedforward neural networks

Cited by in corpus (3)

• Stochastic control of spiking activity bump expansion: monotonic and resonant phenomena
• Propagation of extreme events in multiplex neuronal networks
• Multiplexing-based control of wavefront propagation: the interplay of inter-layer coupling, asymmetry and noise