摘要： In the study of networked systems, a method that can extract information about how the individual nodes are connected with one another would be valuable. In this paper, we present a method that can yield such information of network connectivity using measurements of the dynamics of the nodes as the only input data. Our method is built upon a noise-induced relation between the Laplacian matrix of the network and the dynamical covariance matrix of the nodes, and applies to networked dynamical systems in which the coupling between nodes is uniform and bidirectional. Using examples of different networks and dynamics, we demonstrate that the method can give accurate connectivity information for a wide range of noise amplitude and coupling strength. Moreover, we can calculate a parameter Δ using again only the input of time-series data, and assess the accuracy of the extracted connectivity information based on the value of Δ. 其他題名： Phys Rev E Stat Nonlin Soft Matter Phys 出版者： United States 出版日期： 2013-10 出處： Physical review. E, Statistical, nonlinear, and soft matter physics, 2013-10, Vol.88 (4), p.042817, Article 042817 識別號： ISSN: 1539-3755 識別號： ISSN: 1550-2376 識別號： EISSN: 1550-2376 識別號： DOI: 10.1103/PhysRevE.88.042817 識別號： PMID: 24229235
