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32

CORR
2008
Springer

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Iterative Hard Thresholding for Compressed Sensing

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Iterative Hard Thresholding for Compressed Sensing

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Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present a theoretical analysis of the iterative hard thresholding algorithm when applied to the compressed sensing recovery problem. We show that the algorithm has the following properties (made more precise in the main text of the paper)

Thomas Blumensath, Mike E. Davies

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Added	09 Dec 2010
Updated	09 Dec 2010
Type	Journal
Year	2008
Where	CORR
Authors	Thomas Blumensath, Mike E. Davies

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