  In most compressive sensing problems l1 norm is used during the signal
reconstruction process. In this article the use of entropy functional is
proposed to approximate the l1 norm. A modified version of the entropy
functional is continuous, differentiable and convex. Therefore, it is possible
to construct globally convergent iterative algorithms using Bregman's row
action D-projection method for compressive sensing applications. Simulation
examples are presented.
