• DocumentCode
    83201
  • Title

    An RIP-Based Approach to \\Sigma \\Delta Quantization for Compressed Sensing

  • Author

    Joe-Mei Feng ; Krahmer, Felix

  • Author_Institution
    Inst. for Numerical & Appl. Math., Univ. of Gottingen, Gottingen, Germany
  • Volume
    21
  • Issue
    11
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    1351
  • Lastpage
    1355
  • Abstract
    In this letter, we provide a new approach to estimating the error of reconstruction from ΣΔ quantized compressed sensing measurements. Our method is based on the restricted isometry property (RIP) of a certain projection of the measurement matrix. Our result yields simple proofs and a slight generalization of the best-known reconstruction error bounds for Gaussian and subGaussian measurement matrices.
  • Keywords
    compressed sensing; matrix algebra; quantisation (signal); signal reconstruction; ΣΔ quantized compressed sensing measurements; Gaussian measurement matrices; RIP-based approach; error estimation; measurement matrix; reconstruction error bounds; restricted isometry property; subGaussian measurement matrices; Accuracy; Compressed sensing; Measurement uncertainty; Minimization; Quantization (signal); Random variables; Vectors; $Sigma Delta $ quantization; compressed sensing; restricted isometry property;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2014.2336700
  • Filename
    6849950
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=83201