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TIT
2010
112views Education» more  TIT 2010»
13 years 3 months ago
Exponential bounds implying construction of compressed sensing matrices, error-correcting codes, and neighborly polytopes by ran
In [12] the authors proved an asymptotic sampling theorem for sparse signals, showing that n random measurements permit to reconstruct an N-vector having k nonzeros provided n >...
David L. Donoho, Jared Tanner
CORR
2008
Springer
161views Education» more  CORR 2008»
13 years 7 months ago
Compressed Sensing of Analog Signals
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...
Yonina C. Eldar
ICASSP
2011
IEEE
13 years 24 days ago
Lorentzian based iterative hard thresholding for compressed sensing
In this paper we propose a robust iterative hard thresolding (IHT) algorithm for reconstructing sparse signals in the presence of impulsive noise. To address this problem, we use ...
Rafael E. Carrillo, Kenneth E. Barner
PAMI
2012
11 years 11 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
BMVC
2010
13 years 7 months ago
Moving Camera Registration for Multiple Camera Setups in Dynamic Scenes
Many practical applications require an accurate knowledge of the extrinsic calibration (i.e., pose) of a moving camera. The existing SLAM and structure-from-motion solutions are n...
Evren Imre, Jean-Yves Guillemaut, Adrian Hilton