Applications on Signal Recovering

Recent theoretical developments have generated a great deal of interest in sparse signal representation. A full-rank matrix generates an undetermined system of linear equations.
Our purpose is to find the sparsest solution. i.e., the one with the fewest nonzero entries. Finding sparse representations ultimately requires solving for the sparsest solution of an undetermined system of linear equations. Some recently works had shown that the minimum l1-norm solution to an undetermined linear system is also the sparsest solution to that system under some conditions.

linear system
minimization problem
fixed-point method