Eur. Phys. J. B (2016) 89: 55
https://doi.org/10.1140/epjb/e2016-60956-2

Regular Article

Global and partitioned reconstructions of undirected complex networks

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

^a e-mail: kfcao163@163.com

Received: 12 December 2015
Received in final form: 18 January 2016
Published online: 2 March 2016

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.