Mathematics – Numerical Analysis
Scientific paper
2008-03-17
Mathematics
Numerical Analysis
30 pages. Revised. Presented at Information Theory and Applications, 31 January 2008, San Diego
Scientific paper
Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery algorithm called CoSaMP that delivers the same guarantees as the best optimization-based approaches. Moreover, this algorithm offers rigorous bounds on computational cost and storage. It is likely to be extremely efficient for practical problems because it requires only matrix-vector multiplies with the sampling matrix. For many cases of interest, the running time is just O(N*log^2(N)), where N is the length of the signal.
Needell Deanna
Tropp Joel A.
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