Compressed Sensing for Distributed Systems

  • Giulio Coluccia
  • Chiara Ravazzi
  • Enrico Magli

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Also part of the SpringerBriefs in Signal Processing book sub series (BRIEFSSIGNAL)

Table of contents

  1. Front Matter
    Pages i-x
  2. Giulio Coluccia, Chiara Ravazzi, Enrico Magli
    Pages 1-4
  3. Giulio Coluccia, Chiara Ravazzi, Enrico Magli
    Pages 5-16
  4. Giulio Coluccia, Chiara Ravazzi, Enrico Magli
    Pages 17-37
  5. Giulio Coluccia, Chiara Ravazzi, Enrico Magli
    Pages 39-53
  6. Giulio Coluccia, Chiara Ravazzi, Enrico Magli
    Pages 55-95
  7. Giulio Coluccia, Chiara Ravazzi, Enrico Magli
    Pages 97-97

About this book

Introduction

This book presents a survey of the state-of-the art in the exciting and timely topic of compressed sensing for distributed systems. It has to be noted that, while compressed sensing has been studied for some time now, its distributed applications are relatively new. Remarkably, such applications are ideally suited to exploit all the benefits that compressed sensing can provide. The objective of this book is to provide the reader with a comprehensive survey of this topic, from the basic concepts to different classes of centralized and distributed reconstruction algorithms, as well as a comparison of these techniques. This book collects different contributions on these aspects. It presents the underlying theory in a complete and unified way for the first time, presenting various signal models and their use cases. It contains a theoretical part collecting latest results in rate-distortion analysis of distributed compressed sensing, as well as practical implementations of algorithms obtaining performance close to the theoretical bounds. It presents and discusses various distributed reconstruction algorithms, summarizing the theoretical reconstruction guarantees and providing a comparative analysis of their performance and complexity. In summary, this book will allow the reader to get started in the field of distributed compressed sensing from theory to practice. We believe that this book can find a broad audience among researchers, scientists, or engineers with very diverse backgrounds, having interests in mathematical optimization, network systems, graph theoretical methods, linear systems, stochastic systems, and randomized algorithms. To help the reader become familiar with the theory and algorithms presented, accompanying software is made available on the authors’ web site, implementing several of the algorithms described in the book. The only background required of the reader is a good knowledge of advanced calculus and linear algebra.

Keywords

Compressed Sensing Distributed Optimization Distributed Systems Joint Reconstruction Linear Inverse Problems

Authors and affiliations

  • Giulio Coluccia
    • 1
  • Chiara Ravazzi
    • 2
  • Enrico Magli
    • 3
  1. 1.Electronics and TelecommunicationsPolytechnic University of TurinTurinItaly
  2. 2.Electronics and TelecommunicationsPolytechnic University of TurinTurinItaly
  3. 3.Electronics and TelecommunicationsPolytechnic University of TurinTurinItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-287-390-3
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-287-389-7
  • Online ISBN 978-981-287-390-3
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • About this book