Research output: Contribution to journal › Article › Scientific › peer-review
Distributed autoregressive moving average graph filters. / Loukas, Andreas; Simonetto, Andrea; Leus, Geert.
In: IEEE Signal Processing Letters, Vol. 22, No. 11, 2015, p. 1931-1935.Research output: Contribution to journal › Article › Scientific › peer-review
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TY - JOUR
T1 - Distributed autoregressive moving average graph filters
AU - Loukas, Andreas
AU - Simonetto, Andrea
AU - Leus, Geert
PY - 2015
Y1 - 2015
N2 - We introduce the concept of autoregressive moving average (ARMA) filters on a graph and show how they can be implemented in a distributed fashion. Our graph filter design philosophy is independent of the particular graph, meaning that the filter coefficients are derived irrespective of the graph. In contrast to finite-impulse response (FIR) graph filters, ARMA graph filters are robust against changes in the signal and/or graph. In addition, when time-varying signals are considered, we prove that the proposed graph filters behave as ARMA filters in the graph domain and, depending on the implementation, as first or higher order ARMA filters in the time domain.
AB - We introduce the concept of autoregressive moving average (ARMA) filters on a graph and show how they can be implemented in a distributed fashion. Our graph filter design philosophy is independent of the particular graph, meaning that the filter coefficients are derived irrespective of the graph. In contrast to finite-impulse response (FIR) graph filters, ARMA graph filters are robust against changes in the signal and/or graph. In addition, when time-varying signals are considered, we prove that the proposed graph filters behave as ARMA filters in the graph domain and, depending on the implementation, as first or higher order ARMA filters in the time domain.
KW - Distributed time-varying computations
KW - graph filters
KW - graph Fourier transform
KW - signal processing on graphs
U2 - 10.1109/LSP.2015.2448655
DO - 10.1109/LSP.2015.2448655
M3 - Article
VL - 22
SP - 1931
EP - 1935
JO - IEEE Signal Processing Letters
T2 - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
SN - 1070-9908
IS - 11
ER -
ID: 3495797