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Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
- J. Tropp, A. Gilbert
- Computer ScienceIEEE Transactions on Information Theory
- 1 August 2007
This paper demonstrates theoretically and empirically that a greedy algorithm called orthogonal matching pursuit (OMP) can reliably recover a signal with m nonzero entries in dimension d given O(m ln…
Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions
- N. Halko, P. Martinsson, J. Tropp
- Computer ScienceSIAM Rev.
- 22 September 2009
TLDR
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
- J. Tropp, D. Needell
- Computer ScienceCommun. ACM
- 16 March 2008
TLDR
Greed is good: algorithmic results for sparse approximation
- J. Tropp
- Computer ScienceIEEE Transactions on Information Theory
- 1 October 2004
TLDR
User-Friendly Tail Bounds for Sums of Random Matrices
- J. Tropp
- MathematicsFound. Comput. Math.
- 25 April 2010
TLDR
Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit
- J. Tropp, A. Gilbert, M. Strauss
- Computer ScienceSignal Process.
- 1 March 2006
An Introduction to Matrix Concentration Inequalities
- J. Tropp
- MathematicsFound. Trends Mach. Learn.
- 7 January 2015
TLDR
Just relax: convex programming methods for identifying sparse signals in noise
- J. Tropp
- Computer ScienceIEEE Transactions on Information Theory
- 1 March 2006
TLDR
Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals
- J. Tropp, J. Laska, Marco F. Duarte, J. Romberg, Richard Baraniuk
- Computer ScienceIEEE Transactions on Information Theory
- 30 January 2009
TLDR
SIGNAL RECOVERY FROM PARTIAL INFORMATION VIA ORTHOGONAL MATCHING PURSUIT
- J. Tropp, A. Gilbert
- Computer Science
- 2005
This article demonstrates theoretically and empirically that a greedy algorithm called Orthogonal Matching Pursuit (OMP) can reliably recover a signal with m nonzero entries in dimension d given O(m…
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