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We have developed an approximate signal recovery algorithm with low computational cost for compressed sensing on the basis of randomly constructed sparse measurement matrices.
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A. Maleki and D. L. Donoho, “Optimal iterative thresholding algorithms,” in Proc. of signal Processing with Adaptive Sparse Representations, SPARS 09
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M. Akçakaya, J. Park and V. Tarokh, “Compressive Sensing Using Low Density Frames” Preprint
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Cited in the paper.