Buch, Englisch, 300 Seiten, Format (B × H): 175 mm x 250 mm, Gewicht: 734 g
Buch, Englisch, 300 Seiten, Format (B × H): 175 mm x 250 mm, Gewicht: 734 g
ISBN: 978-1-108-42813-2
Verlag: Cambridge University Press
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.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
Weitere Infos & Material
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.
