21 search results - page 3 / 5 » On the recovery of nonnegative sparse vectors from sparse me... |
CORR
2010
Springer
13 years 3 months ago
2010
Springer
1 minimization can be used to recover sufficiently sparse unknown signals from compressed linear measurements. In fact, exact thresholds on the sparsity, as a function of the ratio...
ICASSP
2009
IEEE
14 years 12 days ago
2009
IEEE
Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse respo...
ICASSP
2008
IEEE
14 years 3 days ago
2008
IEEE
Compressive sensing aims to recover a sparse or compressible signal from a small set of projections onto random vectors; conventional solutions involve linear programming or greed...
ICCV
1999
IEEE
14 years 7 months ago
1999
IEEE
In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques ...
CISS
2011
IEEE
12 years 9 months ago
2011
IEEE
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...