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

link: http://arxiv.org/abs/1105.6138
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.

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