28 search results - page 4 / 6 » Double sparsity: learning sparse dictionaries for sparse sig... |
84
Voted
ICASSP
2009
IEEE
15 years 4 months ago
2009
IEEE
This paper addresses source separation from a linear mixture under two assumptions: source sparsity and orthogonality of the mixing matrix. We propose efficient sparse separation...
ICASSP
2011
IEEE
14 years 1 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...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
82
Voted
CORR
2008
Springer
14 years 9 months ago
2008
Springer
We present a convex formulation of dictionary learning for sparse signal decomposition. Convexity is obtained by replacing the usual explicit upper bound on the dictionary size by...