Graph signal processing: foundations and emerging directions [from the guest editors]

Marques, Antonio G.; Kiyavash, Negar; Moura, Jose M.F.; Van De Ville, Dimitri; Willett, Rebecca

doi:10.1109/MSP.2020.3020715

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Title		Graph signal processing: foundations and emerging directions [from the guest editors]
Authors		Marques, Antonio G. Kiyavash, Negar Moura, Jose M.F. Van De Ville, Dimitri Willett, Rebecca
Published in		IEEE signal processing magazine. 2020, vol. 37, no. 6, p. 11-13
Abstract		The articles in this special section focus on graph signal processing. Generically, the networks that sustain our societies can be understood as complex systems formed by multiple nodes, where global network behavior arises from local interactions between connected nodes. More succinctly, a network or a graph can be defined as a structure that encodes relationships between pairs of elements of a set. The simplicity of this definition drives the application of graphs and networks to a wide variety of disciplines, such as biology, medicine, psychology, sociology, economics, engineering, computer science, and so on.
Keywords		Special issues and sections — Graphic models — Signal processing algorithms — Computer applications
Identifiers		DOI: 10.1109/MSP.2020.3020715
Full text		Article (Published version) (6 MB) - Free access Other version: https://ieeexplore.ieee.org/document/9244183/
Structures		Faculté de médecine / Section de médecine clinique / Département de radiologie et informatique médicale
Research group		Traitement d'images médicales (893)
Citation (ISO format)		MARQUES, Antonio G. et al. Graph signal processing: foundations and emerging directions [from the guest editors]. In: IEEE Signal Processing Magazine, 2020, vol. 37, n° 6, p. 11-13. doi: 10.1109/MSP.2020.3020715 https://archive-ouverte.unige.ch/unige:156902