Stochastic resonance in adaptive dynamical networks
Abstract
The role of adaptive coupling in controlling collective noise-induced dynamics is demonstrated on an example of stochastic resonance in an ensemble of coupled overdamped bistable oscillators. Specifically, it is found that tuning the adaptive coupling parameters allows one to either enhance or suppress stochastic resonance and to shift the optimal noise intensity that yields the most regular stochastic oscillations. All the revealed effects are studied in numerical simulations for two kinds of adaptive coupling models. The first one is a simplified, phenomenological model designed such that the coupling becomes stronger for oscillators with larger differences between their dynamical variables (two configurations for local interaction and one option for global coupling are under consideration). The second one is a local memristive coupling model that provides a physically motivated realization of adaptive interactions with similar properties. In all the considered cases, adaptive coupling is shown to be a flexible stochastic resonance control tool, both in the absence and in the presence of the static coupling component.
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BibTeX
@misc{semenov2026stochastic,
title = {{Stochastic resonance in adaptive dynamical networks}},
author = {Vladimir V. Semenov},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.11367},
eprint = {2610.11367},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.11367},
note = {CC0},
}
RIS
TY - UNPB
TI - Stochastic resonance in adaptive dynamical networks
AU - Vladimir V. Semenov
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2610.11367
UR - https://arxiv.org/abs/2610.11367
AB - The role of adaptive coupling in controlling collective noise-induced dynamics is demonstrated on an example of stochastic resonance in an ensemble of coupled overdamped bistable oscillators. Specifically, it is found that tuning the adaptive coupling parameters allows one to either enhance or suppress stochastic resonance and to shift the optimal noise intensity that yields the most regular stochastic oscillations. All the revealed effects are studied in numerical simulations for two kinds of adaptive coupling models. The first one is a simplified, phenomenological model designed such that the coupling becomes stronger for oscillators with larger differences between their dynamical variables (two configurations for local interaction and one option for global coupling are under consideration). The second one is a local memristive coupling model that provides a physically motivated realization of adaptive interactions with similar properties. In all the considered cases, adaptive coupling is shown to be a flexible stochastic resonance control tool, both in the absence and in the presence of the static coupling component.
ER -