395 search results - page 3 / 79 » Analysis SimCO Algorithms for Sparse Analysis Model Based Di... |
ICML
2009
IEEE
14 years 6 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...
SIAMIS
2010
13 years 1 days ago
2010
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
CVPR
2011
IEEE
12 years 9 months ago
2011
IEEE
Dictionary learning is a challenging theme in computer vision. The basic goal is to learn a sparse representation from an overcomplete basis set. Most existing approaches employ a...
ICIP
2009
IEEE
14 years 6 months ago
2009
IEEE
Recently morphological diversity and sparsity have emerged as new and effective sources of diversity for Blind Source Separation. Based on these new concepts, novel methods such a...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
In the past decade there has been a great interest in a synthesis-based model for signals, based on sparse and redundant representations. Such a model assumes that the signal of i...