Autoregressive moving average graph filter design

Autoregressive moving average graph filter design

Liu, J. (TU Delft Signal Processing Systems)
Isufi, E. (TU Delft Signal Processing Systems)
Leus, G.J.T. (TU Delft Signal Processing Systems)

2018

In graph signal processing, signals are processed by explicitly taking into account their underlying structure, which is generally characterized by a graph. In this field, graph filters play a major role to process such signals in the so-called graph frequency domain. In this paper, we focus on the design of autoregressive moving average (ARMA) graph filters and basically present two design approaches. The first approach is inspired by Prony's method, which considers a modified error between the modeled and the desired frequency response. The second approach is based on an iterative method, which finds the filter coefficients by iteratively minimizing the true error (instead of the modified error) between the modeled and the desired frequency response. The performance of the proposed design algorithms is evaluated and compared with finite impulse response (FIR) graph filters. The obtained results show that ARMA filters outperform FIR filters in terms of approximation accuracy even for the same computational cost.

Finite impulse response filters
Frequency response
Frequency-domain analysis
Autoregressive processes
Laplace equations
Matrix decomposition

http://resolver.tudelft.nl/uuid:98a60e0a-58de-4af5-b23f-5f603d699839

https://doi.org/10.1109/GlobalSIP.2017.8309028

IEEE, Piscataway

2021-11-25

978-1-5090-5991-1

2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017: Proceedings

5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017, 2017-11-14 → 2017-11-16, Montreal, Canada

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2018 J. Liu, E. Isufi, G.J.T. Leus