Adapted Compressed Sensing for Effective Hardware Implementations A Design Flow for Signal-Level Optimization of Compressed Sensing Stages /

This book describes algorithmic methods and hardware implementations that aim to help realize the promise of Compressed Sensing (CS), namely the ability to reconstruct high-dimensional signals from a properly chosen low-dimensional "portrait". The authors describe a design flow and some lo...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Mangia, Mauro (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Pareschi, Fabio (http://id.loc.gov/vocabulary/relators/aut), Cambareri, Valerio (http://id.loc.gov/vocabulary/relators/aut), Rovatti, Riccardo (http://id.loc.gov/vocabulary/relators/aut), Setti, Gianluca (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
Έκδοση:1st ed. 2018.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Chapter 1. Introduction to Compressed Sensing: Fundamentals and Guarantees
  • Chapter 2.How (Well) Compressed Sensing Works in Practice
  • Chapter 3. From Universal to Adapted Acquisition: Rake that Signal!
  • Chapter 4.The Rakeness Problem with Implementation and Complexity Constraints
  • Chapter 5.Generating Raking Matrices: a Fascinating Second-Order Problem
  • Chapter 6.Architectures for Compressed Sensing
  • Chapter 7.Analog-to-information Conversion
  • Chapter 8.Low-complexity Biosignal Compression using Compressed Sensing
  • Chapter 9.Security at the analog-to-information interface using Compressed Sensing.