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CORR
2010
Springer
14 years 10 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...
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CORR
2011
Springer
14 years 1 months ago
2011
Springer
We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A such that for any x, given A...
ICASSP
2008
IEEE
15 years 4 months ago
2008
IEEE
Compressive Sensing (CS) is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compres...
ICASSP
2009
IEEE
15 years 4 months ago
2009
IEEE
— We study the inversion of a random field from pointwise measurements collected by a sensor network. We assume that the field has a sparse representation in a known basis. To ...
DCC
2008
IEEE
15 years 9 months ago
2008
IEEE
There are two main classes of decoding algorithms for "compressed sensing," those which run time time polynomial in the signal length and those which use sublinear resou...