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...
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...
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...
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...
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...