Finite impulse response (FIR) graph filters play a crucial role in the field of signal processing on graphs. However, when the graph signal is time-varying, the state of the art FIR graph filters do not capture the time variations of the input signal. In this work, we propose an extension of FIR graph filters to capture also the signal variations over time. By considering also the past values of the graph signal, the proposed FIR graph filter extends naturally to a 2-dimensional filter, capturing jointly the signal variations over the graph and time. As a particular case of interest we focus on 2-dimensional separable graph-temporal filters, which can be implemented in a distributed fashion at the price of higher communication costs. This allows us to give filter specifications and perform the design independently in the graph and temporal domain. The work is concluded by analyzing the proposed approach for stochastic graph signals, where the first and second order moments of the output signal are characterized.

Original languageEnglish
Title of host publication2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages405-409
Number of pages5
ISBN (Electronic)978-1-5090-4545-7
DOIs
Publication statusPublished - Dec 2016
EventGlobalSIP 2016: 2016 IEEE Global Conference on Signal and Information Processing - Washington, DC, United States
Duration: 7 Dec 20169 Dec 2016
http://2016.ieeeglobalsip.org/

Conference

ConferenceGlobalSIP 2016
Abbreviated titleGlobalSIP
CountryUnited States
CityWashington, DC
Period7/12/169/12/16
Internet address

    Research areas

  • Finite impulse response filters, Two dimensional displays, Frequency response, Transfer functions, Frequency-domain analysis, Laplace equations

ID: 28023934