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Graph Signal Processing: Overview, Challenges, and Applications | IEEE Journals & Magazine | IEEE Xplore

Graph Signal Processing: Overview, Challenges, and Applications


Abstract:

Research in graph signal processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper, we first provide an overview of cor...Show More

Abstract:

Research in graph signal processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper, we first provide an overview of core ideas in GSP and their connection to conventional digital signal processing, along with a brief historical perspective to highlight how concepts recently developed in GSP build on top of prior research in other areas. We then summarize recent advances in developing basic GSP tools, including methods for sampling, filtering, or graph learning. Next, we review progress in several application areas using GSP, including processing and analysis of sensor network data, biological data, and applications to image processing and machine learning.
Published in: Proceedings of the IEEE ( Volume: 106, Issue: 5, May 2018)
Page(s): 808 - 828
Date of Publication: 25 April 2018

ISSN Information:


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