172 search results - page 14 / 35 » Support Recovery of Sparse Signals |
TSP
2010
14 years 4 months ago
2010
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
ICASSP
2009
IEEE
15 years 4 months 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
15 years 3 months ago
2008
IEEE
Classical sampling records the signal level at pre-determined time instances, usually uniformly spaced. An alternative implicit sampling model is to record the timing of pre-deter...
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ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
—Nuclear norm minimization (NNM) has recently gained attention for its use in rank minimization problems. In this paper, we define weak, sectional and strong recovery for NNM to...