论文标题
具有广义扩散耦合网络的光谱识别
Spectral identification of networks with generalized diffusive coupling
论文作者
论文摘要
光谱网络识别旨在从测量数据中推断网络Laplacian矩阵的特征值。这允许从几个节点的本地测量结果捕获有关网络结构的全局信息。在本文中，我们考虑了矢量值扩散耦合的广义设置中的光谱网络识别问题。研究了此问题的可行性，并获得了相关广义特征值问题的理论结果。最后，我们提出了一种数值方法来解决广义网络识别问题，该问题依赖于动态模式分解并利用上述理论结果。
Spectral network identification aims at inferring the eigenvalues of the Laplacian matrix of a network from measurement data. This allows to capture global information on the network structure from local measurements at a few number of nodes. In this paper, we consider the spectral network identification problem in the generalized setting of a vector-valued diffusive coupling. The feasibility of this problem is investigated and theoretical results on the properties of the associated generalized eigenvalue problem are obtained. Finally, we propose a numerical method to solve the generalized network identification problem, which relies on dynamic mode decomposition and leverages the above theoretical results.
