On the Design of Deterministic Matrices for Fast Recovery of Fourier Compressible Functions

  • Authors:
  • J. Bailey;M. A. Iwen;C. V. Spencer

  • Affiliations:
  • jamespb@ksu.edu and cvs@math.ksu.edu;markiwen@math.duke.edu;-

  • Venue:
  • SIAM Journal on Matrix Analysis and Applications
  • Year:
  • 2012

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Abstract

We present a general class of compressed sensing matrices which are then demonstrated to have associated sublinear-time sparse approximation algorithms. We then develop methods for constructing specialized matrices from this class which are sparse when multiplied with a discrete Fourier transform matrix. Ultimately, these considerations improve previous sampling requirements for deterministic sparse Fourier transform methods.