Abstract. In this paper, we empirically investigate the NP-hard problem of finding sparsest solutions to linear equation systems, i.e., solutions with as few nonzeros as possible. ...
A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
Jeffrey D. Blanchard, Coralia Cartis, Jared Tanner...
An underdetermined linear system of equations Ax = b with non-negativity constraint x 0 is considered. It is shown that for matrices A with a row-span intersecting the positive o...
Alfred M. Bruckstein, Michael Elad, Michael Zibule...
Abstract. In this paper, a new algorithm for source recovery in underdetermined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented i...
Hadi Zayyani, Massoud Babaie-Zadeh, G. Hosein Mohi...
Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least a...