Distributed edge-variant graph filters

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

14 Citations (Scopus)

Abstract

The main challenges distributed graph filters face in practice are the communication overhead and computational complexity. In this work, we extend the state-of-the-art distributed finite impulse response (FIR) graph filters to an edge-variant (EV) version, i.e., a filter where every node weights the signals from its neighbors with different values. Besides having the potential to reduce the filter order leading to amenable communication and complexity savings, the EV graph filter generalizes the class of classical and node-variant FIR graph filters. Numerical tests validate our findings and illustrate the potential of the EV graph filters to (i) approximate a user-provided frequency response; and (ii) implement distributed consensus with much lower orders than its direct contenders.

Original languageEnglish
Title of host publication2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Electronic)978-1-5386-1251-4
ISBN (Print)978-1-5386-1252-1
DOIs
Publication statusPublished - 2018
Event2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing - Willemstad, Curaçao
Duration: 10 Dec 201713 Dec 2017
Conference number: 7
http://www.cs.huji.ac.il/conferences/CAMSAP17/

Workshop

Workshop2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
Abbreviated titleCAMSAP
CountryCuraçao
CityWillemstad
Period10/12/1713/12/17
Internet address

Keywords

  • Edge-variant filters
  • finite-time consensus
  • FIR graph filters
  • graph filters
  • graph signal processing

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