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This paper establishes a nearly optimal algorithm for estimating the frequencies and amplitudes of a mixture of sinusoids from noisy equispaced samples.
1941
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1982
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1986
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1989
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1989
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1992
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M. Vetterli, P. Marziliano, and T. Blu, “Sampling signals with finite rate of innovation,” IEEE Trans. on Signal Processing
2002
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E. Dolan and J. Moré, “Benchmarking optimization software with performance profiles,” Mathematical Programming
2002
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G. Zweig, “Super-resolution fourier transforms by optimisation, and isar imaging,” in IEE Proc. on Radar, Sonar and Navigation
2003
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D. L. Donoho and M. Elad, “Optimally sparse representation in general (nonorthogonal) dictionaries via 1 minimization,” Proceedings of the National Academy of Sciences
2003
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Pearson/Prentice Hall, 2005
P. Stoica and R. Moses, Spectral analysis of signals · 2005
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D. Malioutov, M. Çetin, and A. Willsky, “A sparse signal reconstruction perspective for source localization with sensor arrays,” IEEE Trans. on Signal Processing
2005
Cited alongside, same era.
E. J. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inform. Theory
2006
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F. Bunea, A. Tsybakov, and M. Wegkamp, “Sparsity oracle inequalities for the Lasso,” Electronic Journal of Statistics
2007
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S. Bourguignon, H. Carfantan, and J. Idier, “A sparsity-based method for the estimation of spectral lines from irregularly sampled data,” IEEE Journal of Selected Topics in Signal Processing
2007
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T. Blu, P. Dragotti, M. Vetterli, P. Marziliano, and L. Coulot, “Sparse sampling of signal innovations,” Signal Processing Magazine, IEEE
E. J. Candès and Y. Plan, “A probabilistic and RIPless theory of compressed sensing,” IEEE Trans. on Information Theory
2011
Later among the works it cites.
S. Boyd, N. Parikh, B. P. E. Chu, and J. Eckstein, “Distributed optimization and statistical learning via the alternating direction method of multipliers,” Foundations and Trends in Machine Learning
2011
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2012
Later among the works it cites.
2012
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E. J. Candès and M. A. Davenport, “How well can we estimate a sparse vector?,” Applied and Computational Harmonic Analysis
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2008
Cited alongside, same era.
P. J. Bickel, Y. Ritov, and A. B. Tsybakov, “Simultaneous analysis of lasso and dantzig selector,” The Annals of Statistics
2009
Cited alongside, same era.
E. J. Candès and Y. Plan, “Near-ideal model selection by ℓ 1 \ell_{1} minimization,” The Annals of Statistics
2009
Cited alongside, same era.
E. Candès and B. Recht, “Exact matrix completion via convex optimization,” Foundations of Computational Mathematics
2009
Cited alongside, same era.
E. J. Candès and Y. Plan, “Near-ideal model selection by 1 minimization,” The Annals of Statistics
2009
Cited alongside, same era.
R. Baraniuk, V. Cevher, M. Duarte, and C. Hegde, “Model-based compressive sensing,” IEEE Trans. on Information Theory
2010
Cited alongside, same era.
G. Raskutti, M. J. Wainwright, and B. Yu, “Minimax rates of estimation for high-dimensional linear regression over ℓ q \ell_{q} balls.,” IEEE Transactions on Information Theory
2011
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R. de Prony, “Essai experimental et analytique,” J. Ec. Polytech.(Paris)
Cited in the paper.
2012
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2012
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V. Chandrasekaran, B. Recht, P. A. Parrilo, and A. S. Willsky, “The convex geometry of linear inverse problems,” Foundations of Computational Mathematics
2012
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2012
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Y. de Castro and F. Gamboa, “Exact reconstruction using Beurling minimal extrapolation,” Journal of Mathematical Analysis and Applications
2012
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2013
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