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CORR
2010
Springer
128views Education» more  CORR 2010»
13 years 7 months ago
Blind Compressed Sensing
The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measuremen...
Sivan Gleichman, Yonina C. Eldar
CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 7 months ago
Compressed Sensing with Coherent and Redundant Dictionaries
This article presents novel results concerning the recovery of signals from undersampled data in the common situation where such signals are not sparse in an orthonormal basis or ...
Emmanuel J. Candès, Yonina C. Eldar, Deanna...
ICASSP
2011
IEEE
12 years 11 months ago
Computationally efficient regularized acoustic imaging
Sparse recovery techniques have been shown to produce very accurate acoustic images, significantly outperforming traditional deconvolution approaches. However, so far these propo...
Flavio P. Ribeiro, Vitor H. Nascimento
CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 4 months ago
Real-time Robust Principal Components' Pursuit
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
Chenlu Qiu, Namrata Vaswani
ICA
2007
Springer
14 years 1 months ago
Sparse Component Analysis in Presence of Noise Using an Iterative EM-MAP Algorithm
Abstract. In this paper, a new algorithm for source recovery in underdetermined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented i...
Hadi Zayyani, Massoud Babaie-Zadeh, G. Hosein Mohi...