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» An Efficient Method for Compressed Sensing
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TIP
2010
127views more  TIP 2010»
13 years 6 months ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
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
ICASSP
2008
IEEE
14 years 2 months ago
Distributed compressed sensing: Sparsity models and reconstruction algorithms using annihilating filter
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
Ali Hormati, Martin Vetterli
ECCV
2008
Springer
14 years 9 months ago
Compressive Structured Light for Recovering Inhomogeneous Participating Media
We propose a new method named compressive structured light for recovering inhomogeneous participating media. Whereas conventional structured light methods emit coded light patterns...
Jinwei Gu, Shree K. Nayar, Eitan Grinspun, Peter N...
CORR
2011
Springer
186views Education» more  CORR 2011»
12 years 11 months ago
Blind Compressed Sensing Over a Structured Union of Subspaces
—This paper addresses the problem of simultaneous signal recovery and dictionary learning based on compressive measurements. Multiple signals are analyzed jointly, with multiple ...
Jorge Silva, Minhua Chen, Yonina C. Eldar, Guiller...