Uncovering hidden nodes and hidden links in complex dynamic networks

被引：0
作者：
Zhaoyang Zhang
Xinyu Wang
Haihong Li
Yang Chen
Zhilin Qu
Yuanyuan Mi
Gang Hu
机构：
[1] Ningbo University,Department of Physics, School of Physical Science and Technology
[2] Beijing University of Posts and Telecommunications,School of Science
[3] University of California,Department of Medicine, David Geffen School of Medicine
[4] Chinese Academy of Sciences,Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation
[5] Tsinghua University,Department of Psychology
[6] Beijing Normal University,Department of Physics
来源：
Science China Physics, Mechanics & Astronomy | 2024年 / 67卷
关键词：
networks and genealogical trees; stochastic analysis methods; time series analysis;
D O I：
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中图分类号：
学科分类号：
摘要：
Inferring network structures from available data has attracted much interest in network science; however, in many realistic networks, only some of the nodes are perceptible while others are hidden, making it a challenging task. In this work, we develop a method for reconstructing the network with hidden nodes and links, taking account of fast-varying noise and time-delay interactions. By calculating the correlations of available data with different derivative orders for multiple pairs of accessible nodes, analyzing and integrating the relationships between different correlations, and defining diverse hidden-node-related reconstruction motifs, we can effectively identify the hidden nodes and hidden links in the network.
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