The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Compressed Sensing Off the Grid
Open accessAbstract
This paper investigates the problem of estimating the frequency components of a mixture of s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous work in compressed sensing, the frequencies are not assumed to lie on a grid, but can assume any values in the normalized frequency domain [0, 1]. An atomic norm minimization approach is proposed to exactly recover the unobserved samples and identify the unknown frequencies, which is then reformulated as an exact semidefinite program. Even with this continuous dictionary, it is shown that O(slog s log n) random samples are sufficient to guarantee exact frequency localization with high probability, provided the frequencies are well separated. Extensive numerical experiments are performed to illustrate the effectiveness of the proposed method.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Donoho, D. L. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2006.871582 · Cited by 23,994
Donoho, D. L. (2004) · Cited by 16,703
Candes, E. J., Romberg, J., & Tao, T. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2005.862083 · Cited by 15,639
An Introduction To Compressive Sampling
Candes, E. J., & Wakin, M. B. (2008) · IEEE Signal Processing Magazine · doi:10.1109/msp.2007.914731 · Cited by 10,017
Exact Matrix Completion via Convex Optimization
Candès, E. J., & Recht, B. (2009) · Foundations of Computational Mathematics · doi:10.1007/s10208-009-9045-5 · Cited by 4,877
Self-citationBenchmarking optimization software with performance profiles
Dolan, E. D., & Moré, J. J. (2002) · Mathematical Programming · doi:10.1007/s101070100263 · Cited by 4,412
Compressive Sensing [Lecture Notes]
Baraniuk, R. (2007) · IEEE Signal Processing Magazine · doi:10.1109/msp.2007.4286571 · Cited by 4,177
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
Recht, B., Fazel, M., & Parrilo, P. A. (2010) · SIAM Review · doi:10.1137/070697835 · Cited by 3,471
Self-citationSpectral Analysis of Signals: The Missing Data Case
Wang, Y., Li, J., & Stoica, P. (2005) · Synthesis Lectures on Signal Processing · doi:10.1007/978-3-031-02525-9 · Cited by 2,890
Cited by
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
Chi, Y., Lu, Y. M., & Chen, Y. (2019) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2019.2937282 · Cited by 360
Metadata
- Authors
- Tang, G., Bhaskar, B. N., Shah, P., & Recht, B.
- Venue
- IEEE Transactions on Information Theory
- Published
- 2013-11
- Volume
- 59
- Issue
- 11
- Pages
- 7465-7490
- ISSN
- 0018-9448 (ISSN-L)
- 1557-9654
- OpenAlex
- W2565293665
- Cited by
- 1,163
- References
- 35
- FWCI
- 72.75
- Type
- journal article
- Language
- en
- Open access
- green
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