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CORR
2011
Springer
210views Education» more  CORR 2011»
12 years 10 months ago
Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Guoshen Yu, Guillermo Sapiro
CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 3 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
CIARP
2006
Springer
13 years 7 months ago
Color Texture Segmentation by Decomposition of Gaussian Mixture Model
Abstract. Recently we have proposed Gaussian mixtures as a local statistical model to synthesize artificial textures. We describe the statistical dependence of pixels of a movable ...
Jiri Grim, Petr Somol, Michal Haindl, Pavel Pudil
TSP
2010
12 years 10 months ago
Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...
CORR
2008
Springer
234views Education» more  CORR 2008»
13 years 3 months ago
Bayesian Compressive Sensing via Belief Propagation
Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...
Dror Baron, Shriram Sarvotham, Richard G. Baraniuk