A Novel Method for Sampling Bandlimited Graph Signals

In this paper we propose a novel vertex based sampling method for k-bandlimited signals lying on arbitrary graphs, that has a reasonable computational complexity and results in low reconstruction error. Our goal is to find the smallest set of vertices that can guarantee a perfect reconstruction of any k-bandlimited signal on any connected graph. We propose to iteratively search for the vertices that yield the minimum reconstruction error, by minimizing the maximum eigenvalue of the error covariance matrix using a linear solver. We compare the performance of our method with state-of-the-art sampling strategies and random sampling on graphs. Experimental results show that our method successfully computes the smallest sample sets on arbitrary graphs without any parameter tuning. It provides a small reconstruction error, and is robust to noise.


Published in:
2018 26Th European Signal Processing Conference (Eusipco), 126-130
Presented at:
European Signal Processing Conference (EUSIPCO), Rome, ITALY, Aug 03-07, 2018
Year:
Jan 01 2018
Publisher:
Los Alamitos, IEEE COMPUTER SOC
ISSN:
2076-1465
ISBN:
978-90-827970-1-5
Keywords:
Laboratories:




 Record created 2019-01-25, last modified 2019-01-31


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