TY - JOUR
T1 - Probing complex networks from measured time series
AU - Huang, Liang
AU - Lai, Ying-Cheng
AU - Harrison, Mary Ann F
N1 - Funding Information:
This work was supported by AFOSR under Grant No. FA9550-10-1-0083, and by NSF under Grants No. BECS-1023101 and No. CDI-1026710. L. Huang thanks L. Yang for valuable discussions and acknowledge the support from NSF of China through Grants No. 11005053 and No. 11135001.
PY - 2012/10
Y1 - 2012/10
N2 - We propose a method to detect nodes of relative importance, e.g. hubs, in an unknown network based on a set of measured time series. The idea is to construct a matrix characterizing the synchronization probabilities between various pairs of time series and examine the components of the principal eigenvector. We provide a heuristic argument indicating the existence of an approximate one-to-one correspondence between the components and the degrees of the nodes from which measurements are obtained. The striking finding is that such a correspondence appears to be quite robust, which holds regardless of the detailed node dynamics and of the network topology. Our computationally efficient method thus provides a general means to address the important problem of network detection, with potential applications in a number of fields.
AB - We propose a method to detect nodes of relative importance, e.g. hubs, in an unknown network based on a set of measured time series. The idea is to construct a matrix characterizing the synchronization probabilities between various pairs of time series and examine the components of the principal eigenvector. We provide a heuristic argument indicating the existence of an approximate one-to-one correspondence between the components and the degrees of the nodes from which measurements are obtained. The striking finding is that such a correspondence appears to be quite robust, which holds regardless of the detailed node dynamics and of the network topology. Our computationally efficient method thus provides a general means to address the important problem of network detection, with potential applications in a number of fields.
KW - Network detection
KW - time series analysis
KW - topological reconstruction
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U2 - 10.1142/S0218127412502367
DO - 10.1142/S0218127412502367
M3 - Article
AN - SCOPUS:84868485552
SN - 0218-1274
VL - 22
JO - International Journal of Bifurcation and Chaos
JF - International Journal of Bifurcation and Chaos
IS - 10
M1 - 1250236
ER -