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Sampling Signals on Graphs: From Theory to Applications

Yuichi Tanaka, Yonina C. Eldar, Antonio Ortega, Gene Cheung

2020IEEE Signal Processing Magazine144 citationsDOIOpen Access PDF

Abstract

The study of sampling signals on graphs, with the goal of building an analog of sampling for standard signals in the time and spatial domains, has attracted considerable attention recently. Beyond adding to the growing theory on graph signal processing (GSP), sampling on graphs has various promising applications. In this article, we review the current progress on sampling over graphs, focusing on theory and potential applications.

Topics & Concepts

Computer scienceSampling theorySampling (signal processing)Graph theoryAlgorithmTheoretical computer scienceMathematicsTelecommunicationsStatisticsDetectorSample size determinationCombinatoricsAdvanced Graph Neural NetworksMachine Learning and AlgorithmsComplex Network Analysis Techniques
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