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» Bayesian Compressive Sensing for clustered sparse signals
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ICIP
2001
IEEE
14 years 9 months ago
Bayesian resolution-enhancement framework for transform-coded video
Resolution enhancement for video sequences has always been an attractive application in multimedia signal processing. "Superresolution" methods, that combine non-redunda...
Bahadir K. Gunturk, Yucel Altunbasak, Russell M. M...
SIAMIS
2011
13 years 2 months ago
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Stephen Becker, Jérôme Bobin, Emmanue...
TSP
2010
13 years 2 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
ICASSP
2010
IEEE
13 years 7 months ago
Empirical quantization for sparse sampling systems
We propose a quantization design technique (estimator) suitable for new compressed sensing sampling systems whose ultimate goal is classification or detection. The design is base...
Michael A. Lexa
CORR
2010
Springer
116views Education» more  CORR 2010»
13 years 7 months ago
Restricted Isometries for Partial Random Circulant Matrices
In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse an...
Holger Rauhut, Justin K. Romberg, Joel A. Tropp