Adapted compressed sensing for effective hardware implementations : a design flow for signal-level optimization of compressed sensing stages / Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti.
Mangia, Mauro, author.; Pareschi, Fabio, author.; Cambareri, Valerio, author.; Rovatti, Riccardo, author.; Setti, Gianluca, author.
2018
TK5102.9
Available Online

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Title
Adapted compressed sensing for effective hardware implementations : a design flow for signal-level optimization of compressed sensing stages / Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti.
ISBN
9783319613734 (electronic book)
3319613731 (electronic book)
9783319613727
DOI
https://doi.org/10.1007/978-3-319-61373-4
Published
Cham, Switzerland : Springer, [2018]
Language
English
Description
1 online resource : ill.
Item Number
10.1007/978-3-319-61373-4 doi
Call Number
TK5102.9
Dewey Decimal Classification
621.382/2
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed July 25, 2017).
Added Author
Mangia, Mauro, author.
Pareschi, Fabio, author.
Cambareri, Valerio, author.
Rovatti, Riccardo, author.
Setti, Gianluca, author.
Available in Other Form
Print version: 9783319613727
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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.

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