Rational Chebyshev Graph Filters

Oxana Rimleanscaia, Elvin Isufi

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)
80 Downloads (Pure)

Abstract

This paper proposes rational Chebyshev graph filters to approximate step graph spectral responses with arbitrary precision, which are of interest in graph filter banks and spectral clustering. The proposed method relies on the well-known Chebyshev filters of the first kind and on a domain transform of the angular frequencies to the graph frequencies. This approach identifies in closed-form the filter coefficients, hence it avoids the costs of solving a nonlinear problem. Rational Chebyshev graph filters improve the control on the ripples in the pass- and stop-band and on the transition decay. Numerical experiments show the proposed approach approximates better ideal step responses than competing alternatives and reaches the performance of the ideal filters in compressive spectral clustering.

Original languageEnglish
Title of host publicationConference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
EditorsMichael B. Matthews
PublisherIEEE
Pages736-740
Number of pages5
ISBN (Electronic)9780738131269
DOIs
Publication statusPublished - 2020
Event54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020 - Pacific Grove, United States
Duration: 1 Nov 20205 Nov 2020

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2020-November
ISSN (Print)1058-6393

Conference

Conference54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
Country/TerritoryUnited States
CityPacific Grove
Period1/11/205/11/20

Keywords

  • Graph filters
  • graph signal processing
  • spectral clustering

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