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Graph Structure Similarity using Spectral Graph Theory
2016In understanding an unknown network we search for metrics to determine how close an inferred network that is being analyzed, is to the truth. We develop a metric to test for similarity between an inferred network and the true network. Our method uses the eigenvalues of the adjacency matrix and of the Laplacian at each step of the network discovery to ...
Brian Crawford +4 more
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Spectral Graph Theory and Network Dependability
2009 Fourth International Conference on Dependability of Computer Systems, 2009The paper introduces methods of graph theory for ranking substations of an electric power grid. In particular, spectral graph theory is used and several ranking algorithms are described.
Alvaro Torres, George Anders
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Insomnia Characterization: From Hypnogram to Graph Spectral Theory
IEEE Transactions on Biomedical Engineering, 2016To quantify and differentiate control and insomnia sleep onset patterns through biomedical signal processing of overnight polysomnograms.The approach consisted of three tandem modules: 1) biosignal processing module, which used state-space time-varying autoregressive moving average (TVARMA) processes with recursive particle filter, 2) hypnogram ...
Ramiro, Chaparro-Vargas +4 more
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Spectral Integral Variation of Graph Theory
Asian Journal of Mathematics and Computer ResearchSpectral integral variation in graph theory explores the interplay between the spectral properties of graphs and their topological and geometrical characteristics. This study focuses on the eigenvalues and eigenvectors of graph-related matrices, such as the adjacency matrix and the Laplacian matrix, and their implications for understanding graph ...
Hawa Ahmed Alrawayati, Ümit Tokeşer
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Spectral graph theory and deep learning on graphs
2017A significant challenge in machine learning problems is learning meaningful repre- sentations that encode all the information that is relevant to a given task. Neural networks focus on learning parameters based on the ability to successfully represent individual samples of a dataset.
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Algorithm Design Using Spectral Graph Theory
2013Spectral graph theory is the interplay between linear algebra and combinatorial graph theory. Laplace’s equation and its discrete form, the Laplacian matrix, appear ubiquitously in mathematical physics. Due to the recent discovery of very fast solvers for these equations, they are also becoming increasingly useful in combinatorial optimization ...
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Quantifying leaf optical properties with spectral invariants theory
Remote Sensing of Environment, 2021Shengbiao Wu, Yelu Zeng, Qinhuo Liu
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