A Mathematical introduction to compressive sensing /
At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domai...
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| Main Authors: | , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
2013.
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| Series: | Applied and Numerical Harmonic Analysis,
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| Subjects: | |
| Online Access: | Click here to view the full text content |
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Table of Contents:
- 1 An Invitation to Compressive Sensing
- 2 Sparse Solutions of Underdetermined Systems
- 3 Basic Algorithms
- 4 Basis Pursuit
- 5 Coherence
- 6 Restricted Isometry Property
- 7 Basic Tools from Probability Theory
- 8 Advanced Tools from Probability Theory
- 9 Sparse Recovery with Random Matrices
- 10 Gelfand Widths of l1-Balls
- 11 Instance Optimality and Quotient Property
- 12 Random Sampling in Bounded Orthonormal Systems
- 13 Lossless Expanders in Compressive Sensing
- 14 Recovery of Random Signals using Deterministic Matrices
- 15 Algorithms for l1-Minimization
- Appendix A Matrix Analysis
- Appendix B Convex Analysis
- Appendix C Miscellanea
- List of Symbols
- References.