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SIAMIS
2011
14 years 4 months ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang
ICIP
2009
IEEE
15 years 10 months ago
Monotone Operator Splitting For Optimization Problems In Sparse Recovery
This work focuses on several optimization problems involved in recovery of sparse solutions of linear inverse problems. Such problems appear in many fields including image and sig...
CVPR
2010
IEEE
15 years 6 months ago
Increasing depth resolution of Electron Microscopy of Neural circuits using Sparse Tomographic reconstruction
Future progress in neuroscience hinges on reconstruction of neuronal circuits to the level of individual synapses. Because of the specifics of neuronal architecture, imaging must ...
Ashok Veeraraghavan, Alex Genkin, Shiv Vitaladevun...
TIP
2010
255views more  TIP 2010»
14 years 4 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
CISS
2011
IEEE
14 years 1 months ago
Stable manifold embeddings with operators satisfying the Restricted Isometry Property
—Signals of interests can often be thought to come from a low dimensional signal model. The exploitation of this fact has led to many recent interesting advances in signal proces...
Han Lun Yap, Michael B. Wakin, Christopher J. Roze...