Global and partitioned reconstructions of undirected complex networks

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• 作者：Ming Xu ; Chuan-Yun Xu ; Huan Wang ; Yong-Kui Li…
• 关键词：Statistical and Nonlinear Physics
• 刊名：The European Physical Journal B - Condensed Matter
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：89
• 期：3
• 全文大小：323 KB
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• 作者单位：Ming Xu (1) (2)
  Chuan-Yun Xu (1)
  Huan Wang (3)
  Yong-Kui Li (1)
  Jing-Bo Hu (1)
  Ke-Fei Cao (1)
  
  1. Center for Nonlinear Complex Systems, Department of Physics, School of Physics and Astronomy, Yunnan University, Kunming, Yunnan, 650091, P.R. China
  2. School of Mathematical Sciences, Kaili University, Kaili, Guizhou, 556011, P.R. China
  3. School of Computer Science and Technology, Baoji University of Arts and Sciences, Baoji, Shaanxi, 721016, P.R. China
  
• 刊物类别：Physics and Astronomy
• 刊物主题：Physics
  Condensed Matter
  Physics
  Complexity
  Fluids
  Solid State Physics and Spectroscopy
  Superconductivity, Superfluidity and Quantum Fluids
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1434-6036

文摘

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.