Uncovering hidden nodes and hidden links in complex dynamic networks

被引：0

作者：

Zhaoyang Zhang ^{[1
]}

Xinyu Wang ^{[2
,3
]}

Haihong Li ^{[2
]}

Yang Chen ^{[4
]}

Zhilin Qu ^{[3
]}

Yuanyuan Mi ^{[5
]}

Gang Hu ^{[6
]}

机构：

[1] Department of Physics, School of Physical Science and Technology, Ningbo University

[2] School of Science, Beijing University of Posts and Telecommunications

[3] Department of Medicine, David Geffen School of Medicine, University of California

[4] Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences

[5] Department of Psychology, Tsinghua University

[6] Department of Physics, Beijing Normal University

来源：

Science China(Physics,Mechanics & Astronomy) | 2024年 / Mechanics & Astronomy)卷 / 04期

基金：

中国国家自然科学基金; 美国国家卫生研究院; 中央高校基本科研业务费专项资金资助;

关键词：

D O I：

暂无

中图分类号：

O157.5 [图论];

学科分类号：

070104 ;

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.

引用

页码：55 / 67

页数：13

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