Autoregressive Moving Average Graph Filter Design

Jiani Liu, E. Isufi, G. Leus

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

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Abstract

To accurately match a finite-impulse response (FIR) graph filter to a desired response, high filter orders are generally required leading to a high implementation cost. Autoregressive moving average (ARMA) graph filters can alleviate this problem but their design is more challenging. In this paper, we focus on ARMA graph filter design for a known graph. The fundamental aim of our ARMA design is to create a good match to the desired response but with less coefficients than a FIR filter. Our design methods are inspired by Prony’s method but using proper modifications to fit the design to the graph context. Compared with FIR graph filters, our ARMA graph filters show better results for the same number of coefficients.
Original languageEnglish
Title of host publicationProceedings of the 37th WIC Symposium on Information Theory in the Benelux and The 6th Joint WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux
EditorsF. Glineur, J. Louveaux
PublisherUniversité Catholique de Louvain, Belgium
Pages219-226
Number of pages8
ISBN (Electronic)978-2-9601884-0-0
Publication statusPublished - 2016
Event37th WIC Symposium on Information Theory in the Benelux / 6th WIC/IEEE SP Symposium on Information Theory and Signal Processing in the Benelux - Université Catholique de Louvain, Louvain, Belgium
Duration: 19 May 201620 May 2016
http://sites.uclouvain.be/sitb2016/

Conference

Conference37th WIC Symposium on Information Theory in the Benelux / 6th WIC/IEEE SP Symposium on Information Theory and Signal Processing in the Benelux
CountryBelgium
CityLouvain
Period19/05/1620/05/16
Internet address

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