Graph Fourier transform based on singular value decomposition of the directed Laplacian

Yang Chen, Cheng Cheng, Qiyu Sun*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

10 Citations (Scopus)

Abstract

The Graph Fourier transform (GFT) is a fundamental tool in graph signal processing. In this paper, based on singular value decomposition of the Laplacian, we introduce a novel definition of GFT on directed graphs, and use the singular values of the Laplacian to carry the notion of graph frequencies. We show that the proposed GFT has its frequencies and frequency components evaluated by solving some constrained minimization problems with low computational cost, and it could represent graph signals with different modes of variation efficiently. Moreover, the proposed GFT is consistent with the conventional GFT in the undirected graph setting, and on directed circulant graphs, it is the classical discrete Fourier transform, up to some rotation, permutation and phase adjustment. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Original languageEnglish
Article number24
JournalSampling Theory, Signal Processing, and Data Analysis
Volume21
Issue number2
Online published2 Aug 2023
DOIs
Publication statusPublished - Dec 2023
Externally publishedYes

Research Keywords

  • Directed graphs
  • Graph Fourier transform
  • Graph signal processing
  • Singular value decomposition

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