@inproceedings{300f601afa644244bc461903e206411c,
title = "Universal distributed sensing via random projections",
abstract = "This paper develops a new framework for distributed coding and compression in sensor networks based on distributed compressed sensing (DCS). DCS exploits both intra-signal and inter-signal correlations through the concept of joint sparsity; just a few measurements of a jointly sparse signal ensemble contain enough information for reconstruction. DCS is well-suited for sensor network applications, thanks to its simplicity, universality, computational asymmetry, tolerance to quantization and noise, robustness to measurement loss, and scalability. It also requires absolutely no intersensor collaboration. We apply our framework to several real world datasets to validate the framework.",
keywords = "Compressed sensing, Correlation, Greedy algorithms, Linear programming, Sensor networks, Sparsity",
author = "Duarte, {Marco F.} and Wakin, {Michael B.} and Dror Baron and Baraniuk, {Richard G.}",
note = "Copyright: Copyright 2011 Elsevier B.V., All rights reserved.; Fifth International Conference on Information Processing in Sensor Networks, IPSN '06 ; Conference date: 19-04-2006 Through 21-04-2006",
year = "2006",
doi = "10.1145/1127777.1127807",
language = "English (US)",
isbn = "1595933344",
series = "Proceedings of the Fifth International Conference on Information Processing in Sensor Networks, IPSN '06",
pages = "177--185",
booktitle = "Proceedings of the Fifth International Conference on Information Processing in Sensor Networks, IPSN '06",
}