| 书目名称 | Compressed Sensing for Distributed Systems |
| 编辑 | Giulio Coluccia,Chiara Ravazzi,Enrico Magli |
| 视频video | |
| 概述 | Maximizes reader insights into the state of the art in distributed compressed sensing.Contains supplementary material on the software that allows readers to readily test and compare reconstruction alg |
| 丛书名称 | SpringerBriefs in Electrical and Computer Engineering |
| 图书封面 |  |
| 描述 | 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 comparat |
| 出版日期 | Book 2015 |
| 关键词 | Compressed Sensing; Distributed Optimization; Distributed Systems; Joint Reconstruction; Linear Inverse |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-287-390-3 |
| isbn_softcover | 978-981-287-389-7 |
| isbn_ebook | 978-981-287-390-3Series ISSN 2191-8112 Series E-ISSN 2191-8120 |
| issn_series | 2191-8112 |
| copyright | The Author(s) 2015 |
发表于 2025-3-21 19:31:10
