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On the Design of Deterministic Matrices for Fast Recovery of Fourier Compressible Functions
2012
SIAM Journal on Matrix Analysis and Applications
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.
doi:10.1137/110835864
fatcat:nsmf6mb6gbhxxi3vft3q5lkv34