Show simple item record

dc.contributor.authorDavenport, Mark A.
Wakin, Michael B.
Duarte, Marco F.
Baraniuk, Richard G.
dc.creatorDuarte, Marco F.
Baraniuk, Richard G.
Wakin, Michael B.
Davenport, Mark A.
dc.date.accessioned 2007-10-31T00:43:11Z
dc.date.available 2007-10-31T00:43:11Z
dc.date.issued 2006-05-01
dc.date.submitted 2006-05-01
dc.identifier.citation M. A. Davenport, M. B. Wakin, M. F. Duarte and R. G. Baraniuk, "Sparse Signal Detection from Incoherent Projections," vol. 3, 2006.
dc.identifier.urihttps://hdl.handle.net/1911/19867
dc.description Conference Paper
dc.description.abstract The recently introduced theory of Compressed Sensing (CS) enables the reconstruction or approximation of sparse or compressible signals from a small set of incoherent projections; often the number of projections can be much smaller than the number of Nyquist rate samples. In this paper, we show that the CS framework is information scalable to a wide range of statistical inference tasks. In particular, we demonstrate how CS principles can solve signal detection problems given incoherent measurements without ever reconstructing the signals involved. We specifically study the case of signal dection in strong inference and noise and propose an Incoherent Detection and Estimation Algorithm (IDEA) based on Matching Pursuit. The number of measurements and computations necessary for successful detection using IDEA is significantly lower than that necessary for successful reconstruction. Simulations show that IDEA is very resilient to strong interference, additive noise, and measurement quantization. When combined with random measurements, IDEA is applicable to a wide range of different signal classes.
dc.description.sponsorship National Science Foundation
dc.description.sponsorship Air Force Office of Scientific Research
dc.description.sponsorship Office of Naval Research
dc.language.iso eng
dc.subjectCS principles
dc.subject.otherDSP for Communications
dc.title Sparse Signal Detection from Incoherent Projections
dc.type Conference paper
dc.date.note 2006-07-24
dc.citation.bibtexName inproceedings
dc.date.modified 2006-07-24
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)
dc.subject.keywordCS principles
dc.citation.volumeNumber 3
dc.citation.location Toulouse, France
dc.citation.conferenceName IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.2006.1660651
dc.citation.firstpage III-305
dc.citation.lastpage III-308


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1327]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

Show simple item record