Global and partitioned reconstructions of undirected complex networks

  • Ming Xu
  • Chuan-Yun Xu
  • Huan Wang
  • Yong-Kui Li
  • Jing-Bo Hu
  • Ke-Fei Cao
Regular Article

DOI: 10.1140/epjb/e2016-60956-2

Cite this article as:
Xu, M., Xu, CY., Wang, H. et al. Eur. Phys. J. B (2016) 89: 55. doi:10.1140/epjb/e2016-60956-2

Abstract

It is a significant challenge to predict the network topology from a small amount of dynamical observations. Different from the usual framework of the node-based reconstruction, two optimization approaches (i.e., the global and partitioned reconstructions) are proposed to infer the structure of undirected networks from dynamics. These approaches are applied to evolutionary games occurring on both homogeneous and heterogeneous networks via compressed sensing, which can more efficiently achieve higher reconstruction accuracy with relatively small amounts of data. Our approaches provide different perspectives on effectively reconstructing complex networks.

Keywords

Statistical and Nonlinear Physics 

Copyright information

© EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Ming Xu
    • 1
    • 2
  • Chuan-Yun Xu
    • 1
  • Huan Wang
    • 3
  • Yong-Kui Li
    • 1
  • Jing-Bo Hu
    • 1
  • Ke-Fei Cao
    • 1
  1. 1.Center for Nonlinear Complex Systems, Department of Physics, School of Physics and Astronomy, Yunnan UniversityYunnanP.R. China
  2. 2.School of Mathematical Sciences, Kaili UniversityGuizhouP.R. China
  3. 3.School of Computer Science and Technology, Baoji University of Arts and SciencesShaanxiP.R. China