38 search results - page 1 / 8 » Iteratively reweighted algorithms for compressive sensing |
ICASSP
2008
IEEE
14 years 5 months ago
2008
IEEE
The theory of compressive sensing has shown that sparse signals can be reconstructed exactly from many fewer measurements than traditionally believed necessary. In [1], it was sho...
ICASSP
2009
IEEE
14 years 6 months ago
2009
IEEE
We propose a new approach to adaptive system identification when the system model is sparse. The approach applies the ℓ1 relaxation, common in compressive sensing, to improve t...
CORR
2010
Springer
13 years 8 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
2008
IEEE
14 years 5 months 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...
CORR
2008
Springer
13 years 11 months ago
2008
Springer
Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present ...