Wakin, MichaelDuarte, Marco F.Baraniuk, Richard G.Baron, Dror2007-10-312007-10-312006-04-012006-04-01M. Wakin, M. F. Duarte, R. G. Baraniuk and D. Baron, "Universal Distributed Sensing via Random Projections," 2006.https://hdl.handle.net/1911/19866Conference PaperThis 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 inter- sensor collaboration. We apply our framework to several real world datasets to validate the framework.englinear programmingcompressed sensingSparsitygreedy algorithmssensor networkscorrelationDSP for CommunicationsConference paperlinear programmingcompressed sensingSparsitygreedy algorithmssensor networkscorrelationhttp://dx.doi.org/10.1145/1127777.1127807