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ICASSP
2011
IEEE
14 years 1 months ago
Look ahead orthogonal matching pursuit
For compressive sensing, we endeavor to improve the recovery performance of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlyin...
Saikat Chatterjee, Dennis Sundman, Mikael Skoglund
TIT
2010
171views Education» more  TIT 2010»
14 years 4 months ago
Analysis of orthogonal matching pursuit using the restricted isometry property
Orthogonal matching pursuit (OMP) is the canonical greedy algorithm for sparse approximation. In this paper we demonstrate that the restricted isometry property (RIP) can be used f...
Mark A. Davenport, Michael B. Wakin
ICASSP
2009
IEEE
15 years 4 months ago
Separation of a subspace-sparse signal: Algorithms and conditions
In this paper, we show how two classical sparse recovery algorithms, Orthogonal Matching Pursuit and Basis Pursuit, can be naturally extended to recover block-sparse solutions for...
Arvind Ganesh, Zihan Zhou, Yi Ma
TSP
2010
14 years 4 months ago
Block-sparse signals: uncertainty relations and efficient recovery
We consider efficient methods for the recovery of block-sparse signals--i.e., sparse signals that have nonzero entries occurring in clusters--from an underdetermined system of line...
Yonina C. Eldar, Patrick Kuppinger, Helmut Bö...
CORR
2008
Springer
186views Education» more  CORR 2008»
14 years 9 months ago
Greedy Signal Recovery Review
The two major approaches to sparse recovery are L1-minimization and greedy methods. Recently, Needell and Vershynin developed Regularized Orthogonal Matching Pursuit (ROMP) that ha...
Deanna Needell, Joel A. Tropp, Roman Vershynin