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Partial $S$-goodness for partially sparse signal recovery
1. | Department of Applied Mathematics, Beijing Jiaotong University, Beijing 100044, China, China |
2. | Department of Anesthesia, Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Dongcheng District, Beijing 100700, China |
References:
[1] |
A. Bandeira, K. Scheinberg and L. N. Vicente, Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization, Math. Program., 134 (2012), 223-257.
doi: 10.1007/s10107-012-0578-z. |
[2] |
A. Bandeira, K. Scheinberg and L. N. Vicente, On partially sparse recovery, Tech. Rep., 2011. |
[3] |
A. M. Bruckstein, D. L. Donoho and M. Elad, From sparse solutions of systems of equations to sparse modeling of signals and images, SIAM Review, 51 (2009), 34-81.
doi: 10.1137/060657704. |
[4] |
E. J. Candés, J. Romberg and T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Trans. Inform. Theory, 52 (2006), 489-509.
doi: 10.1109/TIT.2005.862083. |
[5] |
E. J. Candés and T. Tao, Decoding by linear programming, IEEE Trans. Inform. Theory, 51 (2005), 4203-4215.
doi: 10.1109/TIT.2005.858979. |
[6] |
E. J. Candés, M. B. Wakin and S. P. Boyd, Enhancing sparsity by reweighted l1 minimization, J Fourier Anal Appl., 14 (2008), 877-905.
doi: 10.1007/s00041-008-9045-x. |
[7] |
D. L. Donoho, Compressed sensing, IEEE Trans. Inform. Theory, 52 (2006), 1289-1306.
doi: 10.1109/TIT.2006.871582. |
[8] |
L. Jacques, A short note on compressed sensing with partially known signal support, Signal Processing, 90 (2010), 3308-3312. |
[9] |
A. Juditsky and A. S. Nemirovski, On verifiable sufficient conditions for sparse signal recovery via l1 minimization, Math. Program., 127 (2011), 57-88.
doi: 10.1007/s10107-010-0417-z. |
[10] |
A. Juditsky, F. Karzan and A. S. Nemirovski, Verifiable conditions of l1-recovery of sparse signals with sign restrictions, Math. Program., 127 (2011), 89-122.
doi: 10.1007/s10107-010-0418-y. |
[11] |
M. A. Khajehnejad, W. Xu, A. S. Avestimehr and B. Hassibi, Analyzing weighted minimization for sparse recovery with nonuniform sparse models, IEEE Trans. Signal Process., 59 (2011), 1985-2001.
doi: 10.1109/TSP.2011.2107904. |
[12] |
A. Majumdar and R. K. Ward, An algorithm for sparse MRI reconstruction by Schatten p-norm minimization, Magnetic Resonance Imaging, 29 (2011), 408-417. |
[13] |
N. Vaswani and W. Lu, Modifed-CS: modifying compressive sensing for problems with partially known support, IEEE Trans. Signal Process., 58 (2010), 4595-4607.
doi: 10.1109/TSP.2010.2051150. |
show all references
References:
[1] |
A. Bandeira, K. Scheinberg and L. N. Vicente, Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization, Math. Program., 134 (2012), 223-257.
doi: 10.1007/s10107-012-0578-z. |
[2] |
A. Bandeira, K. Scheinberg and L. N. Vicente, On partially sparse recovery, Tech. Rep., 2011. |
[3] |
A. M. Bruckstein, D. L. Donoho and M. Elad, From sparse solutions of systems of equations to sparse modeling of signals and images, SIAM Review, 51 (2009), 34-81.
doi: 10.1137/060657704. |
[4] |
E. J. Candés, J. Romberg and T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Trans. Inform. Theory, 52 (2006), 489-509.
doi: 10.1109/TIT.2005.862083. |
[5] |
E. J. Candés and T. Tao, Decoding by linear programming, IEEE Trans. Inform. Theory, 51 (2005), 4203-4215.
doi: 10.1109/TIT.2005.858979. |
[6] |
E. J. Candés, M. B. Wakin and S. P. Boyd, Enhancing sparsity by reweighted l1 minimization, J Fourier Anal Appl., 14 (2008), 877-905.
doi: 10.1007/s00041-008-9045-x. |
[7] |
D. L. Donoho, Compressed sensing, IEEE Trans. Inform. Theory, 52 (2006), 1289-1306.
doi: 10.1109/TIT.2006.871582. |
[8] |
L. Jacques, A short note on compressed sensing with partially known signal support, Signal Processing, 90 (2010), 3308-3312. |
[9] |
A. Juditsky and A. S. Nemirovski, On verifiable sufficient conditions for sparse signal recovery via l1 minimization, Math. Program., 127 (2011), 57-88.
doi: 10.1007/s10107-010-0417-z. |
[10] |
A. Juditsky, F. Karzan and A. S. Nemirovski, Verifiable conditions of l1-recovery of sparse signals with sign restrictions, Math. Program., 127 (2011), 89-122.
doi: 10.1007/s10107-010-0418-y. |
[11] |
M. A. Khajehnejad, W. Xu, A. S. Avestimehr and B. Hassibi, Analyzing weighted minimization for sparse recovery with nonuniform sparse models, IEEE Trans. Signal Process., 59 (2011), 1985-2001.
doi: 10.1109/TSP.2011.2107904. |
[12] |
A. Majumdar and R. K. Ward, An algorithm for sparse MRI reconstruction by Schatten p-norm minimization, Magnetic Resonance Imaging, 29 (2011), 408-417. |
[13] |
N. Vaswani and W. Lu, Modifed-CS: modifying compressive sensing for problems with partially known support, IEEE Trans. Signal Process., 58 (2010), 4595-4607.
doi: 10.1109/TSP.2010.2051150. |
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