Recovery of Sparsely Corrupted Signals
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Helmut Bölcskei | Christoph Studer | Graeme Pope | Patrick Kuppinger | H. Bölcskei | Christoph Studer | G. Pope | Patrick Kuppinger
[1] Julius O. Smith,et al. Restoring a clipped signal , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.
[2] Rémi Gribonval,et al. Sparse representations in unions of bases , 2003, IEEE Trans. Inf. Theory.
[3] Jerry D. Gibson,et al. Digital coding of waveforms: Principles and applications to speech and video , 1985, Proceedings of the IEEE.
[4] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[5] Richard G. Baraniuk,et al. Democracy in Action: Quantization, Saturation, and Compressive Sensing , 2011 .
[6] Jean-Jacques Fuchs,et al. Recovery of exact sparse representations in the presence of bounded noise , 2005, IEEE Transactions on Information Theory.
[7] J. Tropp. On the conditioning of random subdictionaries , 2008 .
[8] Olgica Milenkovic,et al. Subspace Pursuit for Compressive Sensing Signal Reconstruction , 2008, IEEE Transactions on Information Theory.
[9] J. Tropp. On the Linear Independence of Spikes and Sines , 2007, 0709.0517.
[10] Laurent Jacques,et al. A short note on compressed sensing with partially known signal support , 2009, Signal Process..
[11] Patrick Rudolf Emil Kuppinger,et al. General uncertainty relations and sparse signal recovery , 2011 .
[12] MaYi,et al. Dense error correction via l1-minimization , 2010 .
[13] Michael Elad,et al. Stable recovery of sparse overcomplete representations in the presence of noise , 2006, IEEE Transactions on Information Theory.
[14] S. Mallat. A wavelet tour of signal processing , 1998 .
[15] Yonina C. Eldar,et al. Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals , 2007, IEEE Transactions on Signal Processing.
[16] Joel A. Tropp,et al. Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.
[17] Emmanuel J. Candès,et al. Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions , 2004, Found. Comput. Math..
[18] M. Elad,et al. $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.
[19] E. Candès. The restricted isometry property and its implications for compressed sensing , 2008 .
[20] Richard G. Baraniuk,et al. Stable Restoration and Separation of Approximately Sparse Signals , 2011, ArXiv.
[21] Lie Wang,et al. Stable Recovery of Sparse Signals and an Oracle Inequality , 2010, IEEE Transactions on Information Theory.
[22] A. Calderbank,et al. Z4‐Kerdock Codes, Orthogonal Spreads, and Extremal Euclidean Line‐Sets , 1997 .
[23] Charles R. Johnson,et al. Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.
[24] Andrea Montanari,et al. Message-passing algorithms for compressed sensing , 2009, Proceedings of the National Academy of Sciences.
[25] Helmut Bölcskei,et al. Sparse signal recovery from sparsely corrupted measurements , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.
[26] Deanna Needell,et al. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.
[27] Emmanuel J. Candès,et al. Decoding by linear programming , 2005, IEEE Transactions on Information Theory.
[28] Xiaoming Huo,et al. Uncertainty principles and ideal atomic decomposition , 2001, IEEE Trans. Inf. Theory.
[29] D. Donoho,et al. Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA) , 2005 .
[30] Stéphane Mallat,et al. Super-Resolution With Sparse Mixing Estimators , 2010, IEEE Transactions on Image Processing.
[31] S. Agaian. Hadamard Matrices and Their Applications , 1985 .
[32] Arkadi Nemirovski,et al. On sparse representation in pairs of bases , 2003, IEEE Trans. Inf. Theory.
[33] Gitta Kutyniok,et al. Microlocal Analysis of the Geometric Separation Problem , 2010, ArXiv.
[34] A. Bruckstein,et al. K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .
[35] Yonina C. Eldar,et al. Coherence-Based Performance Guarantees for Estimating a Sparse Vector Under Random Noise , 2009, IEEE Transactions on Signal Processing.
[36] Michael P. Friedlander,et al. Probing the Pareto Frontier for Basis Pursuit Solutions , 2008, SIAM J. Sci. Comput..
[37] Saifallah Ghobber,et al. On uncertainty principles in the finite dimensional setting , 2009, ArXiv.
[38] E. Candès,et al. Sparsity and incoherence in compressive sampling , 2006, math/0611957.
[39] Arian Maleki,et al. Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing , 2009, IEEE Journal of Selected Topics in Signal Processing.
[40] Michael Elad,et al. A generalized uncertainty principle and sparse representation in pairs of bases , 2002, IEEE Trans. Inf. Theory.
[41] Y. Bresler. Spectrum-blind sampling and compressive sensing for continuous-index signals , 2008, 2008 Information Theory and Applications Workshop.
[42] D. Donoho,et al. Uncertainty principles and signal recovery , 1989 .
[43] Michael Elad,et al. A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur , 2001, IEEE Trans. Image Process..
[44] Gerald Matz,et al. The effect of unreliable LLR storage on the performance of MIMO-BICM , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.
[45] Zhifeng Zhang,et al. Adaptive time-frequency decompositions , 1994 .
[46] K. Horadam. Hadamard Matrices and Their Applications , 2006 .
[47] Richard G. Baraniuk,et al. Exact signal recovery from sparsely corrupted measurements through the Pursuit of Justice , 2009, 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers.
[48] Michael Elad,et al. A constrained matching pursuit approach to audio declipping , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[49] Ping Feng,et al. Spectrum-blind minimum-rate sampling and reconstruction of multiband signals , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.
[50] Robert W. Heath,et al. Designing structured tight frames via an alternating projection method , 2005, IEEE Transactions on Information Theory.
[51] John Wright,et al. Dense Error Correction Via $\ell^1$-Minimization , 2010, IEEE Transactions on Information Theory.
[52] Y. C. Pati,et al. Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition , 1993, Proceedings of 27th Asilomar Conference on Signals, Systems and Computers.
[53] Kenneth E. Barner,et al. Robust Sampling and Reconstruction Methods for Sparse Signals in the Presence of Impulsive Noise , 2010, IEEE Journal of Selected Topics in Signal Processing.
[54] Guillermo Sapiro,et al. Image inpainting , 2000, SIGGRAPH.
[55] Helmut Bölcskei,et al. Uncertainty Relations and Sparse Signal Recovery for Pairs of General Signal Sets , 2011, IEEE Transactions on Information Theory.
[56] Wei Lu,et al. Modified-CS: Modifying compressive sensing for problems with partially known support , 2009, 2009 IEEE International Symposium on Information Theory.
[57] Helmut Bölcskei,et al. Where is randomness needed to break the square-root bottleneck? , 2010, 2010 IEEE International Symposium on Information Theory.
[58] Trac D. Tran,et al. Exact Recoverability From Dense Corrupted Observations via $\ell _{1}$-Minimization , 2011, IEEE Transactions on Information Theory.
[59] Joel A. Tropp,et al. Just relax: convex programming methods for identifying sparse signals in noise , 2006, IEEE Transactions on Information Theory.
[60] Michael Elad,et al. Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[61] Christoph Studer,et al. Probabilistic Recovery Guarantees for Sparsely Corrupted Signals , 2012, IEEE Transactions on Information Theory.
[62] Richard Baraniuk,et al. Compressive Domain Interference Cancellation , 2009 .
[63] S. Mallat,et al. Adaptive greedy approximations , 1997 .