Introduction to Graph Signal Processing
Introduction to Graph Signal Processing
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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.
- Focuses on the fundamentals of graph signal processing
- Shows how graph signal processing tools can be applied to a range of different application areas
- Includes numerous exercises and Matlab examples, and accompanied online by a solutions manual for instructors
Product details
June 2022Adobe eBook Reader
9781108640176
0 pages
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- 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.
