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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Foucart, Simon (Autor), Rauhut, Holger (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Birkhäuser, 2013.
Edición:1st ed. 2013.
Colección:Applied and Numerical Harmonic Analysis,
Temas:
Mathematics-Data processing.
Signal processing.
Computer science-Mathematics.
Telecommunication.
Functional analysis.
Computational Science and Engineering.
Signal, Speech and Image Processing .
Mathematical Applications in Computer Science.
Communications Engineering, Networks.
Functional Analysis.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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