441 search results - page 3 / 89 » Sparse Recovery Using Sparse Random Matrices |
114
Voted
NIPS
2008
15 years 2 months ago
2008
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
113
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FOCS
2008
IEEE
15 years 7 months ago
2008
IEEE
Abstract— We consider the approximate sparse recovery problem, where the goal is to (approximately) recover a highdimensional vector x ∈ Rn from its lower-dimensional sketch Ax...
138
Voted
ESANN
2004
15 years 2 months ago
2004
We propose an algorithm for recovering the matrix A in X = AS where X is a random vector of lower dimension than S. S is assumed to be sparse in the sense that S has less nonzero e...
106
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CORR
2010
Springer
15 years 1 months ago
2010
Springer
In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse an...
114
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ICASSP
2011
IEEE
14 years 4 months ago
2011
IEEE
Compressed sensing is a novel technique where one can recover sparse signals from the undersampled measurements. In this paper, a K × N measurement matrix for compressed sensing ...