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» Support Recovery of Sparse Signals
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ICASSP
2011
IEEE
14 years 1 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
TSP
2008
146views more  TSP 2008»
14 years 9 months ago
Improved M-FOCUSS Algorithm With Overlapping Blocks for Locally Smooth Sparse Signals
Abstract-- The FOCal Underdetermined System Solver (FOCUSS) algorithm has already found many applications in signal processing and data analysis, whereas the regularized MFOCUSS al...
Rafal Zdunek, Andrzej Cichocki
ICA
2007
Springer
15 years 3 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...
SIGPRO
2011
209views Hardware» more  SIGPRO 2011»
14 years 4 months ago
Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
A. Rakotomamonjy
TSP
2010
14 years 4 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic