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  Dynamical network size estimation from local observations

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

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 ???ViewItemFull_lblCreators???:
Tang, Xiuchuan1, ???ENUM_CREATORROLE_AUTHOR???
Huo, Wei1, ???ENUM_CREATORROLE_AUTHOR???
Yuan, Ye1, ???ENUM_CREATORROLE_AUTHOR???
Li, Xiuting1, ???ENUM_CREATORROLE_AUTHOR???
Shi, Ling1, ???ENUM_CREATORROLE_AUTHOR???
Ding, Han1, ???ENUM_CREATORROLE_AUTHOR???
Kurths, Jürgen2, ???ENUM_CREATORROLE_AUTHOR???           
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 ???ViewItemFull_lblAbstract???:

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.

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 ???ViewItemFull_lblDates???: 2020-08-122020-09-142020
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.1088/1367-2630/abaf2f
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???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Complex Networks
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Nonlinear Dynamics
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_WORKINGGROUP???: Network- and machine-learning-based prediction of extreme events
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???ViewItemFull_lblSourceTitle???: New Journal of Physics
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