title: Repeated-drive adaptive feedback identification of network topologies.
abstract: The identification of the topological structures of complex networks from dynamical information is a significant inverse problem. How to infer the information of network topology from short-time dynamical data is a challenging topic. The presence of synchronization among nodes makes the identification of network topology difficult. In this paper we present an efficient method called the repeated-drive adaptive feedback scheme to reveal the network connectivity from short-time dynamics. By applying the short asynchronous transient data as a repeated drive, the adjacency matrix can be successfully determined in terms of the modified adaptive feedback scheme. This improved scheme is valid for both synchronous and asynchronous cases of the network and is especially efficient in the presence of global or local synchronization, where the transient drive can be obtained by perturbing the system to get a very short asynchronous transient. The detection speed of our scheme exhibits the optimized effect by adjusting the time-series segment length and the coupling strength among nodes in the network.
authors.affiliation: Department of Physics and the Beijing-Hong Kong-Singapore Joint Center for Nonlinear and Complex Studies, Beijing Normal University, Beijing 100875, China and Journal Editorial Department, Henan Normal University, Xinxiang 453007, China.
authors.forename: Pu
authors.initials: P
authors.lastname: Yang
authors.affiliation: Department of Physics and the Beijing-Hong Kong-Singapore Joint Center for Nonlinear and Complex Studies, Beijing Normal University, Beijing 100875, China.
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zheng