TR2010-002

Signal Processing with Compressive Measurements


    •  Davenport, A., Boufounos, P.T., Wakin, B., Baraniuk, G., "Signal Processing with Compressive Measurements", IEEE Journal of Selected Topics in Signal Processing, pp. 445-460, February 2010.
      BibTeX TR2010-002 PDF
      • @article{Davenport2010feb,
      • author = {Davenport, A. and Boufounos, P.T. and Wakin, B. and Baraniuk, G.},
      • title = {Signal Processing with Compressive Measurements},
      • journal = {IEEE Journal of Selected Topics in Signal Processing},
      • year = 2010,
      • pages = {445--460},
      • month = feb,
      • issn = {1932-4533},
      • url = {https://www.merl.com/publications/TR2010-002}
      • }
  • MERL Contact:
  • Research Area:

    Computational Sensing

The recently introduced theory of compressive sensing enables the recovery of sparse or compressive 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 near-optimal measurement scheme. This has inspired the design of hardware systems that directly implement random measurement protocols. However, despite the intense focus of the community on signal recovery, many (if not most) signal processing problems do not require full signal recovery. In this paper, we take some first steps in the direction of solving inference problems - such as detection, classification, or estimation - and filtering problems using only compressive measurements and without ever reconstructing the signals involved. We provide theoretical bounds along with experimental results.

 

  • Related News & Events

    •  AWARD   2015 IEEE Signal Processing Society Best Paper Award
      Date: December 1, 2015
      Awarded to: Mark A. Davenport, Petros T. Boufounos, Michael B. Wakin and Richard G. Baraniuk
      MERL Contact: Petros Boufounos
      Research Area: Computational Sensing
      Brief
      • Petros Boufounos is a recipient of the 2015 IEEE Signal Processing Society Best Paper Award for the paper that he co-authored with Mark A. Davenport, Michael B. Wakin and Richard G. Baraniuk on "Signal Processing with Compressive Measurements" which was published in the April 2010 issue of IEEE Journal of Selected Topics in Signal Processing. The Best Paper Award honors the author(s) of a paper of exceptional merit dealing with a subject related to the Society's technical scope, and appearing in one of the Society's solely owned transactions or the Journal of Selected Topics in Signal Processing. Eligibility is based on a five-year window: for example, for the 2015 Award, the paper must have appeared in one of the Society's Transactions between January 1, 2010 and December 31, 2014.
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    •  NEWS   IEEE Journal of Selected Topics in Signal Processing: publication by MERL researchers and others
      Date: February 22, 2010
      Where: IEEE Journal of Selected Topics in Signal Processing
      Research Area: Computational Sensing
      Brief
      • The article "Signal Processing with Compressive Measurements" by Davenport, A., Boufounos, P.T., Wakin, B. and Baraniuk, G. was published in IEEE Journal of Selected Topics in Signal Processing.
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