A Mathematical Introduction to Compressive Sensing

• Κύριοι συγγραφείς: Foucart, Simon (Συγγραφέας), Rauhut, Holger (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York : Imprint: Birkhäuser, 2013.
• Σειρά: Applied and Numerical Harmonic Analysis,
• Θέματα: Mathematics.; Computer science > Mathematics.; Functional analysis.; Computer mathematics.; Electrical engineering.; Computational Science and Engineering.; Signal, Image and Speech Processing.; Math Applications in Computer Science.; Communications Engineering, Networks.; Functional Analysis.

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...

Πίνακας περιεχομένων:

• 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.