12 search results - page 2 / 3 » Exploiting Statistical Dependencies in Sparse Representation... |
ICASSP
2011
IEEE
13 years 2 months ago
2011
IEEE
Consider the decomposition of a signal into features that undergo transformations drawn from a continuous family. Current methods discretely sample the transformations and apply s...
TIT
2010
13 years 5 months ago
2010
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
SIGPRO
2011
13 years 5 months ago
2011
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
CVPR
2010
IEEE
14 years 3 months ago
2010
IEEE
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
ICASSP
2008
IEEE
14 years 5 months ago
2008
IEEE
In the case of multicomponent AM-FM signals, the idealized representation which consists of weighted trajectories on the time-frequency (TF) plane, is intrinsically sparse. Recent...