Abstract

We develop a general method to detect hidden nodes in complex networks, using only time series from nodes that are accessible to external observation. Our method is based on compressive sensing and we formulate a general framework encompassing continuous- and discrete-time and the evolutionary-game type of dynamical systems as well. For concrete demonstration, we present an example of detecting hidden nodes from an experimental social network. Our paradigm for detecting hidden nodes is expected to find applications in a variety of fields where identifying hidden or black-boxed objects based on a limited amount of data is of interest.

Original languageEnglish (US)
Article number065201
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume85
Issue number6
DOIs
StatePublished - Jun 29 2012

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Complex Networks
Time series
games
Vertex of a graph
dynamical systems
Compressive Sensing
Evolutionary Game
Social Networks
Discrete-time
Dynamical system
Paradigm

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Statistics and Probability

Cite this

Detecting hidden nodes in complex networks from time series. / Su, Ri Qi; Wang, Wen Xu; Lai, Ying-Cheng.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 85, No. 6, 065201, 29.06.2012.

Research output: Contribution to journalArticle

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