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TSP
2010
12 years 4 months ago
Distributed sampling of signals linked by sparse filtering: theory and applications
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
ICIP
2006
IEEE
13 years 11 months ago
Robust Kernel Regression for Restoration and Reconstruction of Images from Sparse Noisy Data
We introduce a class of robust non-parametric estimation methods which are ideally suited for the reconstruction of signals and images from noise-corrupted or sparsely collected s...
Hiroyuki Takeda, Sina Farsiu, Peyman Milanfar
ICASSP
2008
IEEE
13 years 4 months ago
Finding needles in noisy haystacks
The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., ļ¬nding needles ...
Rui M. Castro, Jarvis Haupt, Robert Nowak, Gil M. ...
DAGM
2003
Springer
13 years 2 months ago
Splines and Wavelets: New Perspectives for Pattern Recognition
We provide an overview of spline and wavelet techniques with an emphasis on applications in pattern recognition. The presentation is divided in three parts. In the first one, we ar...
Michael Unser
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