An Overview of Spectral Graph Wavelets

Rodney Fonseca ()
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Rodney Fonseca: Weizmann Institute of Science, Department of Computer Science and Applied Mathematics

A chapter in Time Series and Wavelet Analysis, 2024, pp 239-246 from Springer

Abstract: Abstract Many data science problems use data collected from networks. Such data usually involve graph signals, which require methods adapted to take the network structure into account. Wavelet methods are important tools in the statistical and signal processing literature and can boost graph data analysis. This chapter describes how wavelets can be applied to graphs. We focus on the spectral graph wavelet transform, a widely used method in the graph signal processing literature. We provide an overview of this wavelet transform and illustrate its application on real data about COVID-19 in Brazil.

Keywords: Graph signal processing; Graph fourier transform; Laplacian matrix; COVID-19 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-66398-7_12

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DOI: 10.1007/978-3-031-66398-7_12

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