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Journal Article

Dynamical network size estimation from local observations


Tang,  Xiuchuan
External Organizations;

Huo,  Wei
External Organizations;

Yuan,  Ye
External Organizations;

Li,  Xiuting
External Organizations;

Shi,  Ling
External Organizations;

Ding,  Han
External Organizations;


Kurths,  Jürgen
Potsdam Institute for Climate Impact Research;

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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.

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