Adapted Compressed Sensing for Effective Hardware Implementations A
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
- PDF / 11,853,161 Bytes
- 329 Pages / 439.43 x 683.15 pts Page_size
- 41 Downloads / 237 Views
Compressed Sensing for Effective Hardware Implementations A Design Flow for Signal-Level Optimization of Compressed Sensing Stages
Adapted Compressed Sensing for Effective Hardware Implementations
Mauro Mangia • Fabio Pareschi • Valerio Cambareri Riccardo Rovatti • Gianluca Setti
Adapted Compressed Sensing for Effective Hardware Implementations A Design Flow for Signal-Level Optimization of Compressed Sensing Stages
123
Mauro Mangia ARCES Università di Bologna Bologna, Italy
Fabio Pareschi ENDIF Università di Ferrara Ferrara, Italy
Valerio Cambareri ICTEAM/ELEN Université Catholique de Louvain Louvain-la-Neuve, Belgium
Riccardo Rovatti DEI, ARCES Università di Bologna Bologna, Italy
Gianluca Setti ENDIF Università di Ferrara Ferrara, Italy
ISBN 978-3-319-61372-7 ISBN 978-3-319-61373-4 (eBook) DOI 10.1007/978-3-319-61373-4 Library of Congress Control Number: 2017943984 © Springer International Publishing AG 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
To the one and only woman in this book and in my life. Riccardo
Preface
The aim of this book is to give a concrete answer to the following question: Can compressed sensing effectively yield optimized means for signal acquisition, encoding, and encryption, either in analog or digital circuits and systems, when implementation constraints are considered in its realization? The reason why this question is important is that compressed-sensing (CS) has been intensely discussed in the engineering community for more than a decade as a hot research topic, gathering a great deal of effort from a large community that unites scientists in applied mathematics and information theory, as
Data Loading...
