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» Sparse Recovery Using Sparse Random Matrices
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TSP
2010
14 years 4 months ago
Methods for sparse signal recovery using Kalman filtering with embedded pseudo-measurement norms and quasi-norms
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
Avishy Carmi, Pini Gurfil, Dimitri Kanevsky
ICASSP
2011
IEEE
14 years 1 months ago
Sparse video recovery using Linearly Constrained Gradient Projection
This paper concerns the reconstruction of a temporally-varying scene from a video sequence of noisy linear projections. Assuming that each video frame is sparse or compressible in...
Daniel Thompson, Zachary T. Harmany, Roummel F. Ma...
PPAM
2005
Springer
15 years 3 months ago
A New Diagonal Blocking Format and Model of Cache Behavior for Sparse Matrices
Algorithms for the sparse matrix-vector multiplication (shortly SpM×V ) are important building blocks in solvers of sparse systems of linear equations. Due to matrix sparsity, the...
Pavel Tvrdík, Ivan Simecek
SIAMNUM
2011
139views more  SIAMNUM 2011»
14 years 4 months ago
Adaptive Wavelet Schemes for Parabolic Problems: Sparse Matrices and Numerical Results
A simultaneous space-time variational formulation of a parabolic evolution problem is solved with an adaptive wavelet method. This method is shown to converge with the best possibl...
Nabi Chegini, Rob Stevenson
ISCIS
2003
Springer
15 years 3 months ago
An Alternative Compressed Storage Format for Sparse Matrices
The handling of the sparse matrix vector product(SMVP) is a common kernel in many scientific applications. This kernel is an irregular problem, which has led to the development of...
Anand Ekambaram, Eurípides Montagne