Dynamical network size estimation from local observations

Tang, Xiuchuan; Huo, Wei; Yuan, Ye; Li, Xiuting; Shi, Ling; Ding, Han; Kurths, Jürgen

doi:10.1088/1367-2630/abaf2f

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Dynamical network size estimation from local observations

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Tang, Xiuchuan
External Organizations;

Huo, Wei
External Organizations;

Yuan, Ye
External Organizations;

Li, Xiuting
External Organizations;

Shi, Ling
External Organizations;

Ding, Han
External Organizations;

/persons/resource/Juergen.Kurths

Kurths, Jürgen
Potsdam Institute for Climate Impact Research;

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Zitation

Tang, X., Huo, W., Yuan, Y., Li, X., Shi, L., Ding, H., Kurths, J. (2020): Dynamical network size estimation from local observations. - New Journal of Physics, 22, 093031.
https://doi.org/10.1088/1367-2630/abaf2f

Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_24678

Zusammenfassung

Here we present a method to estimate the total number of nodes of a network using locally observed response dynamics. The algorithm has the following advantages: (a) it is data-driven. Therefore it does not require any prior knowledge about the model; (b) it does not need to collect measurements from multiple stimulus; and (c) it is distributed as it uses local information only, without any prior information about the global network. Even if only a single node is measured, the exact network size can be correctly estimated using a single trajectory. The proposed algorithm has been applied to both linear and nonlinear networks in simulation, illustrating the applicability to real-world physical networks.