Dimensionality reduction of networked systems with separable coupling-dynamics: Theory and applications

Chengyi Tu, Ying Fan and Tianyu Shi

Chaos, Solitons & Fractals, 2024, vol. 182, issue C

Abstract: Complex dynamical systems are prevalent in various domains, but their analysis and prediction are hindered by their high dimensionality and nonlinearity. Dimensionality reduction techniques can simplify the system dynamics by reducing the number of variables, but most existing methods do not account for networked systems with separable coupling-dynamics, where the interaction between nodes can be decomposed into a function of the node state and a function of the neighbor state. Here, we propose a novel dimensional reduction framework for networked systems where the coupling-dynamics between nodes are separable. We derive the reduced system's equation and stability conditions, and propose an error metric to quantify the reduction accuracy. We demonstrate our framework on two examples of networked systems with separable coupling-dynamics: a modified susceptible-infected-susceptible model with non-direct infection and a modified Michaelis-Menten model with activation and inhibition. We conduct numerical experiments on synthetic and empirical networks to validate and evaluate our framework, and find a good agreement between the original and reduced systems. We also investigate the effects of different network structures and parameters on the system dynamics and the reduction error. Our framework offers a general and powerful tool for studying complex dynamical networks with separable coupling-dynamics.

Keywords: Dimensionality reduction; Complex dynamical networks; Separable coupling-dynamics (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077924003850
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:182:y:2024:i:c:s0960077924003850

DOI: 10.1016/j.chaos.2024.114833

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().