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CoSaMP: Iterative Signal Recovery from Incomplete and Inaccurate Samples.
- Source :
-
Communications of the ACM . Dec2010, Vol. 53 Issue 12, p93-100. 8p. 3 Charts. - Publication Year :
- 2010
-
Abstract
- Compressive sampling (CoSa) is a new paradigm for developing data sampling technologies. It is based on the principle that many types of vector-space data are compressible, which is a term of art in mathematical signal processing. The key ideas are that randomized dimension reduction preserves the information in a compressible signal and that it is possible to develop hardware devices that implement this dimension reduction efficiently. The main computational challenge in CoSa is to reconstruct a compressible signal from the reduced representation acquired by the sampling device. This extended abstract describes a recent algorithm, called CoSaMP, that accomplishes the data recovery task. It was the first known method to offer near-optimal guarantees on resource usage. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00010782
- Volume :
- 53
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Communications of the ACM
- Publication Type :
- Periodical
- Accession number :
- 55618664
- Full Text :
- https://doi.org/10.1145/1859204.1859229