Introduction to Graph Signal Processing

Antonio Ortega (University of Southern California)

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Hardback

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English

Cambridge University Press
09 June 2022

Computer networking & communications; Machine learning; Pattern recognition; Signal processing; Image processing

An intuitive and accessible text explaining the fundamentals and applications of graph signal processing. Requiring only an elementary understanding of linear algebra, it covers both basic and advanced topics, including node domain processing, graph signal frequency, sampling, and graph signal representations, as well as how to choose a graph. Understand the basic insights behind key concepts and learn how graphs can be associated to a range of specific applications across physical, biological and social networks, distributed sensor networks, image and video processing, and machine learning. With numerous exercises and Matlab examples to help put knowledge into practice, and a solutions manual available online for instructors, this unique text is essential reading for graduate and senior undergraduate students taking courses on graph signal processing, signal processing, information processing, and data analysis, as well as researchers and industry professionals.

By: Antonio Ortega (University of Southern California)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Dimensions: Height: 251mm, Width: 175mm, Spine: 22mm
Weight: 720g
ISBN: 9781108428132
ISBN 10: 1108428134
Pages: 300
Publication Date: 09 June 2022
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

1. Introduction; 2. Node domain processing; 3. Graph signal frequency-Spectral graph theory; 4. Sampling; 5. Graph signal representations; 6. How to choose a graph; 7. Applications; Appendix A. Linear algebra and signal representations; Appendix B. GSP with Matlab: the GraSP toolbox; References; Index.

Antonio Ortega is a Professor of Electrical and Computer Engineering at the University of Southern California, and a Fellow of the IEEE.