38 search results - page 1 / 8 » Iteratively reweighted algorithms for compressive sensing |
ICASSP
2008
IEEE
13 years 11 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
13 years 11 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 2 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
13 years 11 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 5 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 ...