CoSaMP: Iterative signal recovery from incomplete and inaccurate samples Export

@article{citeulike:4236315, abstract = {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.}, archivePrefix = {arXiv}, author = {Needell, D. and Tropp, J. A.}, citeulike-article-id = {4236315}, citeulike-linkout-0 = {http://arxiv.org/abs/0803.2392}, citeulike-linkout-1 = {http://arxiv.org/pdf/0803.2392}, day = {17}, eprint = {0803.2392}, keywords = {compressed-sensing}, month = {Apr}, posted-at = {2009-04-03 18:26:26}, priority = {2}, title = {CoSaMP: Iterative signal recovery from incomplete and inaccurate samples}, url = {http://arxiv.org/abs/0803.2392}, year = {2008} }

TY - JOUR ID - citeulike:4236315 L3 - citeulike-article-id:4236315 N2 - 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. TI - CoSaMP: Iterative signal recovery from incomplete and inaccurate samples KW - compressed-sensing AU - Needell, D AU - Tropp, JA PY - 2008/Apr/17/ UR - http://arxiv.org/abs/0803.2392 ER -