The Fractional Fourier Transform on Graphs: Modulation and Convolution

Yu Zhang, Bing Zhao Li*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The fractional Fourier transform on graph (GFrFT) is an extension of discrete fractional Fourier transform (DFrFT) based on graph signal processing (GSP). In this paper, we discuss the shift, polynomial filters, delta functions, the convolution and modulation of graph signal in fractional domain. First, we review the basic theory of discrete graph signal processing, concepts of graph signals and GFrFT. Then, similar to the definition of the shift of adjacency matrix in vertex domain, the shift matrix of graph spectral domain in the GFrFT is defined. Finally, the new polynomial filters are used to illustrate the convolution and modulation of fractional graph signals in the vertex domain and graph spectral domain, and the relationship between the delta functions and convolution is discussed.

Original languageEnglish
Title of host publication2023 8th International Conference on Signal and Image Processing, ICSIP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages737-741
Number of pages5
ISBN (Electronic)9798350397932
DOIs
Publication statusPublished - 2023
Event8th International Conference on Signal and Image Processing, ICSIP 2023 - Wuxi, China
Duration: 8 Jul 202310 Jul 2023

Publication series

Name2023 8th International Conference on Signal and Image Processing, ICSIP 2023

Conference

Conference8th International Conference on Signal and Image Processing, ICSIP 2023
Country/TerritoryChina
CityWuxi
Period8/07/2310/07/23

Keywords

  • Graph signal processing
  • convolution
  • fractional Fourier transform on graph
  • modulation

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