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Adapted Compressed Sensing for Effective Hardware Implementations : A Design Flow for Signal-Level Optimization of Compressed Sensing Stages / / by Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti



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Autore: Mangia Mauro Visualizza persona
Titolo: Adapted Compressed Sensing for Effective Hardware Implementations : A Design Flow for Signal-Level Optimization of Compressed Sensing Stages / / by Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Edizione: 1st ed. 2018.
Descrizione fisica: 1 online resource (XIV, 319 p. 180 illus., 142 illus. in color.)
Disciplina: 621.3815
Soggetto topico: Electronic circuits
Signal processing
Image processing
Speech processing systems
Electronics
Microelectronics
Circuits and Systems
Signal, Image and Speech Processing
Electronics and Microelectronics, Instrumentation
Persona (resp. second.): PareschiFabio
CambareriValerio
RovattiRiccardo
SettiGianluca
Nota di bibliografia: Includes bibliographical references at the end of each chapters.
Nota di contenuto: 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.
Sommario/riassunto: 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 low-resource physical realizations of sensing systems based on CS. They highlight the pros and cons of several design choices from a pragmatic point of view, and show how a lightweight and mild but effective form of adaptation to the target signals can be the key to consistent resource saving. The basic principle of the devised design flow can be applied to almost any CS-based sensing system, including analog-to-information converters, and has been proven to fit an extremely diverse set of applications. Many practical aspects required to put a CS-based sensing system to work are also addressed, including saturation, quantization, and leakage phenomena.
Titolo autorizzato: Adapted Compressed Sensing for Effective Hardware Implementations  Visualizza cluster
ISBN: 3-319-61373-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299901603321
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