Distributed edge-variant graph filters

Distributed edge-variant graph filters

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

2018

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.

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

http://resolver.tudelft.nl/uuid:8c1e1ede-3d44-4c8b-b0cd-8cbbe7ddc8d4

https://doi.org/10.1109/CAMSAP.2017.8313105

IEEE, Piscataway, NJ

2021-11-25

978-1-5386-1252-1

2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017-12-10 → 2017-12-13, Willemstad, Curaçao

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 Mario Coutino, E. Isufi, G.J.T. Leus