Random Filters for Compressive Sampling and Reconstruction

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dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)en_US
dc.citation.firstpageIII-872en_US
dc.citation.lastpageIII-875en_US
dc.citation.locationToulouse, Franceen_US
dc.citation.volumeNumber3en_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.authorWakin, Michaelen_US
dc.contributor.authorDuarte, Marco F.en_US
dc.contributor.authorTropp, Joel A.en_US
dc.contributor.authorBaron, Droren_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:07:23Zen_US
dc.date.available2007-10-31T01:07:23Zen_US
dc.date.issued2006-05-01en_US
dc.date.modified2006-07-24en_US
dc.date.note2006-07-24en_US
dc.date.submitted2006-05-01en_US
dc.descriptionConference Paperen_US
dc.description.abstractWe propose and study a new technique for efficiently acquiring and reconstructing signals based on convolution with a fixed FIR filter having random taps. The method is designed for sparse and compressible signals, i.e., ones that are well approximated by a short linear combination of vectors from an orthonormal basis. Signal reconstruction involves a non-linear Orthogonal Matching Pursuit algorithm that we implement efficiently by exploiting the nonadaptive, time-invariant structure of the measurement process. While simpler and more efficient than other random acquisition techniques like Compressed Sensing, random filtering is sufficiently generic to summarize many types of compressible signals and generalizes to streaming and continuous-time signals. Extensive numerical experiments demonstrate its efficacy for acquiring and reconstructing signals sparse in the time, frequency, and wavelet domains, as well as piecewise smooth signals and Poisson processes.en_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipAir Force Office of Scientific Researchen_US
dc.description.sponsorshipOffice of Naval Researchen_US
dc.identifier.citationR. G. Baraniuk, M. Wakin, M. F. Duarte, J. A. Tropp and D. Baron, "Random Filters for Compressive Sampling and Reconstruction," vol. 3, 2006.en_US
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.2006.1660793en_US
dc.identifier.urihttps://hdl.handle.net/1911/20399en_US
dc.language.isoengen_US
dc.subjectOrthogonal Matching Pursuit algorithmen_US
dc.subject.keywordOrthogonal Matching Pursuit algorithmen_US
dc.subject.otherDSP for Communicationsen_US
dc.titleRandom Filters for Compressive Sampling and Reconstructionen_US
dc.typeConference paperen_US
dc.type.dcmiTexten_US
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