Overview
- Highlights state-of-the-art applications and methodologies of compressed sensing
- Contains chapters written by leading experts in the fields of compressed sensing and deep learning
- Includes a self-contained introduction to the theory and applications of compressed sensing
Part of the book series: Applied and Numerical Harmonic Analysis (ANHA)
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Table of contents (9 chapters)
Keywords
- Compressed sensing
- Compressed sensing theory and applications
- Compressed sensing book
- Compressed sensing introduction
- Compressed sensing 2019
- Deep learning compressed sensing
- Deep learning book
- Machine learning
- Quantized compressed sensing
- Signal sensing book
- Generalization error machine learning
- MATHEON conference
- information and communication, circuits
About this book
- Quantized compressed sensing
- Classification
- Machine learning
- Oracle inequalities
- Non-convex optimization
- Image reconstruction
- Statistical learning theory
This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.
Editors and Affiliations
Bibliographic Information
Book Title: Compressed Sensing and Its Applications
Book Subtitle: Third International MATHEON Conference 2017
Editors: Holger Boche, Giuseppe Caire, Robert Calderbank, Gitta Kutyniok, Rudolf Mathar, Philipp Petersen
Series Title: Applied and Numerical Harmonic Analysis
DOI: https://doi.org/10.1007/978-3-319-73074-5
Publisher: Birkhäuser Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-319-73073-8Published: 14 August 2019
eBook ISBN: 978-3-319-73074-5Published: 13 August 2019
Series ISSN: 2296-5009
Series E-ISSN: 2296-5017
Edition Number: 1
Number of Pages: XVII, 295
Number of Illustrations: 18 b/w illustrations, 39 illustrations in colour
Topics: Information and Communication, Circuits, Fourier Analysis, Mathematical Applications in Computer Science, Machine Learning, Signal, Image and Speech Processing