Reconstructing propagation networks with natural diversity and identifying hidden sources
نویسندگان
چکیده
منابع مشابه
Reconstructing propagation networks with natural diversity and identifying hidden sources
Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progress in this area, reconstructing networks with stochastic dynamical processes from limited time series remains to be an outstanding problem. Here we develop a framework based on compressed sensing to reconstruct compl...
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Zhesi Shen,1 Wen-Xu Wang,1, 2, ∗ Ying Fan,1 Zengru Di,1 and Ying-Cheng Lai2, 3 1School of Systems Science, Beijing Normal University, Beijing, 100875, P. R. China 2School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USA 3Department of Physics, Arizona State University, Tempe, Arizona 85287, USA. Abstract Our ability to uncover complex network s...
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Node similarity significantly contributes to the growth of real networks. In this paper, based on the observed epidemic spreading results we apply the node similarity metrics to reconstruct the underlying networks hosting the propagation. We find that the reconstruction accuracy of the similarity metrics is strongly influenced by the infection rate of the spreading process. Moreover, there is a...
متن کاملReconstructing propagation networks with temporal similarity metrics
Node similarity is a significant property driving the growth of real networks. In this paper, based on the observed spreading results we apply the node similarity metrics to reconstruct propagation networks. We find that the reconstruction accuracy of the similarity metrics is strongly influenced by the infection rate of the spreading process. Moreover, there is a range of infection rate in whi...
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ژورنال
عنوان ژورنال: Nature Communications
سال: 2014
ISSN: 2041-1723
DOI: 10.1038/ncomms5323