Adapted Compressed Sensing for Effective Hardware Implementations

A Design Flow for Signal-Level Optimization of Compressed Sensing Stages

Nonfiction, Science & Nature, Technology, Electronics, Circuits
Cover of the book Adapted Compressed Sensing for Effective Hardware Implementations by Riccardo Rovatti, Mauro Mangia, Valerio Cambareri, Gianluca Setti, Fabio Pareschi, Springer International Publishing
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Author: Riccardo Rovatti, Mauro Mangia, Valerio Cambareri, Gianluca Setti, Fabio Pareschi ISBN: 9783319613734
Publisher: Springer International Publishing Publication: July 14, 2017
Imprint: Springer Language: English
Author: Riccardo Rovatti, Mauro Mangia, Valerio Cambareri, Gianluca Setti, Fabio Pareschi
ISBN: 9783319613734
Publisher: Springer International Publishing
Publication: July 14, 2017
Imprint: Springer
Language: English

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.

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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.

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