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CORR
2011
Springer
210views Education» more  CORR 2011»
13 years 5 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 10 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
14 years 2 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
13 years 5 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 10 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