1. CoSaMP: Iterative Signal Recovery from Incomplete and Inaccurate Samples.
- Author
-
Needell, Deanna and Tropp, Joel A.
- Subjects
- *
DIGITAL signal processing , *COMPUTER programming , *SIGNAL processing , *STATISTICAL sampling , *SAMPLING (Process) , *COMPUTER science - 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]
- Published
- 2010
- Full Text
- View/download PDF