Global synchronization analysis of non-diffusively coupled networks through Contraction Theory
Fatou K. Ndow, Zahra Aminzare

TL;DR
This paper extends contraction theory to analyze and establish conditions for global synchronization in non-diffusively coupled nonlinear networks, with applications to neuronal models like Hindmarsh-Rose and FitzHugh-Nagumo oscillators.
Contribution
It introduces a novel extension of contraction theory to non-diffusively coupled networks, providing a framework for understanding synchronization in these systems.
Findings
Derived sufficient conditions for global synchronization in non-diffusively coupled networks.
Validated theoretical results on neuronal oscillator models with chemical synapses.
Demonstrated the applicability of the extended contraction theory to biological neural networks.
Abstract
Synchronization of coupled dynamical systems is a widespread phenomenon in both biological and engineered networks, and understanding this behavior is crucial for controlling such systems. Considerable research has been dedicated to identifying the conditions that promote synchronization in diffusively coupled systems, where coupling relies on the difference between the states of neighboring systems and vanishes on the synchronization manifold. In particular, contraction theory provides an elegant method for analyzing synchronization patterns in diffusively coupled networks. However, these approaches do not fully explain the emergence of synchronization behavior in non-diffusively coupled networks where the coupling does not vanish on the synchronization manifold and hence the dynamics on the synchronization manifold differ from the uncoupled systems. Inspired by neuronal networks…
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Taxonomy
TopicsNonlinear Dynamics and Pattern Formation · Neural dynamics and brain function · stochastic dynamics and bifurcation
