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CORR
2011
Springer
194views Education» more  CORR 2011»
14 years 3 months ago
Sparse approximation property and stable recovery of sparse signals from noisy measurements
—In this paper, we introduce a sparse approximation property of order s for a measurement matrix A: xs 2 ≤ D Ax 2 + β σs(x) √ s for all x, where xs is the best s-sparse app...
Qiyu Sun
CORR
2011
Springer
183views Education» more  CORR 2011»
14 years 6 months ago
Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning
— We address the sparse signal recovery problem in the context of multiple measurement vectors (MMV) when elements in each nonzero row of the solution matrix are temporally corre...
Zhilin Zhang, Bhaskar D. Rao
CORR
2008
Springer
98views Education» more  CORR 2008»
14 years 12 months ago
Information-theoretic limits on sparse signal recovery: Dense versus sparse measurement matrices
We study the information-theoretic limits of exactly recovering the support set of a sparse signal, using noisy projections defined by various classes of measurement matrices. Our ...
Wei Wang, Martin J. Wainwright, Kannan Ramchandran
ICMLA
2009
14 years 9 months ago
Mahalanobis Distance Based Non-negative Sparse Representation for Face Recognition
Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some application...
Yangfeng Ji, Tong Lin, Hongbin Zha
ICASSP
2010
IEEE
15 years 14 hour ago
An L1 criterion for dictionary learning by subspace identification
We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
Florent Jaillet, Rémi Gribonval, Mark D. Pl...