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Compressed Sensing (CS) is an appealing framework for applications such as Magnetic Resonance Imaging (MRI).
Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
Emmanuel Candès, Justin Romberg, and Terence Tao · 2006
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Stable signal recovery from incomplete and inaccurate measurements
Emmanuel Candès, Justin Romberg, and Terence Tao · 2006
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Near-optimal signal recovery from random projections: Universal encoding strategies?
Emmanuel Candès and Terence Tao · 2006
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Compressed sensing
David Donoho · 2006
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Just relax: Convex programming methods for identifying sparse signals in noise
Joel A Tropp · 2006
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Sparse MRI: The application of compressed sensing for rapid MR imaging
Michael Lustig, David Donoho, and John M. Pauly · 2007
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An introduction to probability theory and its applications
Willliam Feller · 2008
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Beyond sparsity: Recovering structured representations by { \{ \ \backslash ell } \} ˆ 1 minimization and greedy algorithms
Rémi Gribonval and Morten Nielsen · 2008
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A compressed sensing technique for ofdm channel estimation in mobile environments: Exploiting channel sparsity for reducing pilots
Georg Tauböck and Franz Hlawatsch · 2008
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Robust recovery of signals from a structured union of subspaces
Yonina C Eldar and Moshe Mishali · 2009
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Why do commercial ct scanners still employ traditional, filtered back-projection for image reconstruction?
Xiaochuan Pan, Emil Y Sidky, and Michael Vannier · 2009
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Compressed sensing imaging techniques for radio interferometry
Yves Wiaux, Laurent Jacques, Gilles Puy, Anna MM. Scaife, and Pierre Vandergheynst · 2009
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Model-based compressive sensing
Richard G Baraniuk, Volkan Cevher, Marco F Duarte, and Chinmay Hegde · 2010
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Compressive sensing and structured random matrices
Holger Rauhut · 2010
Cited alongside, same era.
A probabilistic and ripless theory of compressed sensing
Emmanuel Candès and Yaniv Plan · 2011
Cited alongside, same era.
Structured compressed sensing: From theory to applications
Marco F Duarte and Yonina C Eldar · 2011
Cited alongside, same era.
Recovering low-rank matrices from few coefficients in any basis
David Gross · 2011
Cited alongside, same era.
On variable density compressive sampling
Gilles Puy, Pierre Vandergheynst, and Yves Wiaux · 2011
Cited alongside, same era.
Optimization with sparsity-inducing penalties
Francis Bach, Rodolphe Jenatton, Julien Mairal, and Guillaume Obozinski · 2012
Cited alongside, same era.
Sampling and reconstruction of spatial fields using mobile sensors
J. Unnikrishnan and M. Vetterli · 2013
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Sampling high-dimensional bandlimited fields on low-dimensional manifolds
Jayakrishnan Unnikrishnan and Martin Vetterli · 2013
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Ben Adcock, Anders C Hansen, and Bogdan Roman · 2014
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Ben Adcock, Anders C. Hansen, and Bogdan Roman · 2014
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An analysis of blocks sampling strategies in compressed sensing
Jérémie Bigot, Claire Boyer, and Pierre Weiss · 2014
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Spread spectrum magnetic resonance imaging
Gilles Puy, Jose P. Marques, Rolf Gruetter, J. Thiran, Dimitri Van De Ville, Pierre Vandergheynst, and Yves Wiaux · 2012
Cited alongside, same era.
User-friendly tail bounds for sums of random matrices
Joel A. Tropp · 2012
Cited alongside, same era.
Breaking the coherence barrier: A new theory for compressed sensing
Ben Adcock, Anders C. Hansen, Clarice Poon, and Bogdan Roman · 2013
Cited alongside, same era.
Variable density compressed sensing in MRI. theoretical vs heuristic sampling strategies
N. Chauffert, P. Ciuciu, and P. Weiss · 2013
Cited alongside, same era.
A mathematical introduction to compressive sensing
Simon Foucart and Holger Rauhut · 2013
Cited alongside, same era.
Exact recovery conditions for sparse representations with partial support information
Cédric Herzet, Charles Soussen, Jérôme Idier, and Rémi Gribonval · 2013
Cited alongside, same era.
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On the absence of the rip in real-world applications of compressed sensing and the rip in levels
Alexander Bastounis and Anders C Hansen · 2014
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Variable density sampling with continous sampling trajectories
Nicolas Chauffert, Philippe Ciuciu, Jonas Kahn, and Pierre Weiss · 2014
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On minimal trajectories for mobile sampling of bandlimited fields
Karlheinz Gröchenig, José Luis Romero, Jayakrishnan Unnikrishnan, and Martin Vetterli · 2014
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Stable and robust sampling strategies for compressive imaging
Felix Krahmer and Rachel Ward · 2014
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On asymptotic structure in compressed sensing
Bogdan Roman, Anders Hansen, and Ben Adcock · 2014
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Generalized sampling and infinite-dimensional compressed sensing
Ben Adcock and Anders C Hansen · 2015
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Performance bounds for grouped incoherent measurements in compressive sensing
Adam C. Polak, Marco F. Duarte, and Dennis L. Goeckel · 2015
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Gradient waveform design for variable density sampling in magnetic resonance imaging
Nicolas Chauffert, Pierre Weiss, Jonas Kahn, and Philippe Ciuciu · 2016
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