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» Sparse Image Reconstruction using Sparse Priors
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ICML
2006
IEEE
16 years 4 months ago
Regression with the optimised combination technique
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
Jochen Garcke
WSOM
2009
Springer
15 years 10 months ago
Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas
Abstract. We show how the “Online Sparse Coding Neural Gas” algorithm can be applied to a more realistic model of the “Cocktail Party Problem”. We consider a setting where ...
Kai Labusch, Erhardt Barth, Thomas Martinetz
ICASSP
2008
IEEE
15 years 10 months ago
Subspace compressive detection for sparse signals
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
Zhongmin Wang, Gonzalo R. Arce, Brian M. Sadler
TIT
2010
96views Education» more  TIT 2010»
14 years 10 months ago
Beyond Nyquist: efficient sampling of sparse bandlimited signals
Wideband analog signals push contemporary analog-to-digital conversion systems to their performance limits. In many applications, however, sampling at the Nyquist rate is inefficie...
Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Ju...
ECCV
2010
Springer
15 years 9 months ago
Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary
Abstract. By coding the input testing image as a sparse linear combination of the training samples via l1-norm minimization, sparse representation based classification (SRC) has b...