Distributed edge-variant graph filters

Conference paper (2018)

Authors

Mario Coutino Signal Processing Systems -

E. Isufi Signal Processing Systems -

G.J.T. Leus Signal Processing Systems -

Research Group

Signal Processing Systems () (TU Delft)

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

Graph filters Graph signal processing Finite-time consensus Edge-variant filters FIR graph filters

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Published Date

2018

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

Abstract

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.

Files

08313105.pdf

(pdf | 0.251 Mb)

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