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ICASSP
2011
IEEE
10 years 10 months ago
Iterative hard thresholding for compressed sensing with partially known support
Recent works in modified compressed sensing (CS) show that reconstruction of sparse or compressible signals with partially known support yields better results than traditional CS...
Rafael E. Carrillo, Luisa F. Polania, Kenneth E. B...
SIGPRO
2010
135views more  SIGPRO 2010»
11 years 5 months ago
A short note on compressed sensing with partially known signal support
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...
Laurent Jacques
ICASSP
2009
IEEE
12 years 1 months ago
A simple, efficient and near optimal algorithm for compressed sensing
When sampling signals below the Nyquist rate, efficient and accurate reconstruction is nevertheless possible, whenever the sampling system is well behaved and the signal is well ...
Thomas Blumensath, Mike E. Davies
CORR
2010
Springer
97views Education» more  CORR 2010»
11 years 4 months ago
On the Scaling Law for Compressive Sensing and its Applications
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...
Weiyu Xu, Ao Tang
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