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TIT
2008
121views more  TIT 2008»
13 years 7 months ago
Stability Results for Random Sampling of Sparse Trigonometric Polynomials
Recently, it has been observed that a sparse trigonometric polynomial, i.e. having only a small number of non-zero coefficients, can be reconstructed exactly from a small number o...
Holger Rauhut
CORR
2008
Springer
186views Education» more  CORR 2008»
13 years 7 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
CIMAGING
2008
142views Hardware» more  CIMAGING 2008»
13 years 8 months ago
Greedy signal recovery and uncertainty principles
This paper seeks to bridge the two major algorithmic approaches to sparse signal recovery from an incomplete set of linear measurements
Deanna Needell, Roman Vershynin
ICASSP
2009
IEEE
14 years 2 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
DAGM
2008
Springer
13 years 9 months ago
Example-Based Learning for Single-Image Super-Resolution
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...
Kwang In Kim, Younghee Kwon