84 search results - page 10 / 17 » Gradient-Based Methods for Sparse Recovery |
TSP
2010
13 years 2 months ago
2010
We consider efficient methods for the recovery of block-sparse signals--i.e., sparse signals that have nonzero entries occurring in clusters--from an underdetermined system of line...
ICA
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. In this paper, a new algorithm for source recovery in underdetermined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented i...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sens...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measuremen...
CORR
2008
Springer
13 years 7 months ago
2008
Springer
The two major approaches to sparse recovery are L1-minimization and greedy methods. Recently, Needell and Vershynin developed Regularized Orthogonal Matching Pursuit (ROMP) that ha...