Network Resonance Method: Estimating Network Structure from the Resonance of Oscillation Dynamics
Network Resonance Method: Estimating Network Structure from the Resonance of Oscillation Dynamics
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DOI：
10.1587/transcom.2018ebp3160
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发表时间：
2019-04
期刊：
影响因子：
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通讯作者：
Satoshi Furutani;C. Takano;Masaki Aida
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文献类型：
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作者：
Satoshi Furutani;C. Takano;Masaki Aida
谱图理论基于邻接矩阵或拉普拉斯矩阵来表示网络拓扑结构和链路权重，为分析网络结构提供了一种有用的方法。然而，在大规模和复杂的社会网络中，由于很难完全知道网络拓扑和链路权重，我们无法直接确定这些矩阵的组成部分。为了解决这一问题，我们提出了一种利用网络上振荡动力学的共振，通过估计其特征值和特征向量来间接确定拉普拉斯矩阵的方法。关键词：拉普拉斯矩阵，谱图理论，共振
Spectral graph theory, based on the adjacency matrix or the Laplacian matrix that represents the network topology and link weights, provides a useful approach for analyzing network structure. However, in large scale and complex social networks, since it is difficult to completely know the network topology and link weights, we cannot determine the components of these matrices directly. To solve this problem, we propose a method for indirectly determining the Laplacian matrix by estimating its eigenvalues and eigenvectors using the resonance of oscillation dynamics on networks. key words: Laplacian matrix, spectral graph theory, resonance