The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Signal Processing With Compressive Measurements
Abstract
The recently introduced theory of compressive sensing enables the recovery of sparse or compressible signals from a small set of nonadaptive, linear measurements. If properly chosen, the number of measurements can be much smaller than the number of Nyquist-rate samples. Interestingly, it has been shown that random projections are a near-optimal measurement scheme. This has inspired the design of hardware systems that directly implement random measurement protocols. However, despite the intense focus of the community on signal recovery, many (if not most) signal processing problems do not require full signal recovery. In this paper, we take some first steps in the direction of solving inference problems-such as detection, classification, or estimation-and filtering problems using only compressive measurements and without ever reconstructing the signals involved. We provide theoretical bounds along with experimental results.
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Cites
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Robust Face Recognition via Sparse Representation
Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., & Ma, Y. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.79 · Cited by 9,388
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CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
Needell, D., & Tropp, J. A. (2009) · Applied and Computational Harmonic Analysis · doi:10.1016/j.acha.2008.07.002 · Cited by 4,326
The restricted isometry property and its implications for compressed sensing
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Cited by
Cognitive Radio Techniques Under Practical Imperfections: A Survey
Sharma, S. K., Bogale, T. E., Chatzinotas, S., Ottersten, B., Le, L. B., & Wang, X. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2452414 · Cited by 221
Metadata
- Authors
- Davenport, M. A., Boufounos, P. T., Wakin, M. B., & Baraniuk, R. G.
- Venue
- IEEE Journal of Selected Topics in Signal Processing
- Published
- 2010-04
- Volume
- 4
- Issue
- 2
- Pages
- 445-460
- ISSN
- 1932-4553 (ISSN-L)
- 1941-0484
- OpenAlex
- W2120961178
- Cited by
- 623
- References
- 37
- FWCI
- 48.64
- Type
- journal article
- Language
- en
- Open access
- closed
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