Detection and estimation with compressive measurements

dc.contributor.authorBaraniuk, Richard G.
dc.contributor.authorDavenport, Mark A.
dc.contributor.authorWakin, Michael B.
dc.date.accessioned2008-08-07T14:23:55Z
dc.date.available2008-08-07T14:23:55Z
dc.date.issued2006-11-01en
dc.description.abstractThe recently introduced theory of compressed sensing enables the reconstruction of sparse or compressible signals from a small set of nonadaptive, linear measurements. If properly chosen, the number of measurements can be much smaller than the number of Nyquist rate samples. Interestingly, it has been shown that random projections are a satisfactory measurement scheme. This has inspired the design of physical systems that directly implement similar measurement schemes. However, despite the intense focus on the reconstruction of signals, many (if not most) signal processing problems do not require a full reconstruction of the signal { we are often interested only in solving some sort of detection problem or in the estimation of some function of the data. In this report, we show that the compressed sensing framework is useful for a wide range of statistical inference tasks. In particular, we demonstrate how to solve a variety of signal detection and estimation problems given the measurements without ever reconstructing the signals themselves. We provide theoretical bounds along with experimental results.en
dc.description.sponsorshipONR grants N00014-06-1-0769 and N00014-06-1-0829; AFOSR grant FA9550- 04-0148; DARPA grants N66001-06-1-2011 and N00014-06-1-0610; NSF grants CCF-0431150, CNS-0435425, and CNS-0520280; and the Texas Instruments Leadership University Program.en
dc.identifier.citationR. G. Baraniuk, M. A. Davenport and M. B. Wakin, "Detection and estimation with compressive measurements," 2006.
dc.identifier.urihttps://hdl.handle.net/1911/21677
dc.language.isoeng
dc.relation.IsPartOfSeriesRice University ECE Technical Report;TREE 0610
dc.subjectcompressive sensingen
dc.subjectdetectionen
dc.subjectestimationen
dc.titleDetection and estimation with compressive measurementsen
dc.typeReport
dc.type.dcmiText
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