Kose, K.Gunay, O.Çetin, A. Enis2015-07-282015-07-282014-011051-2004http://hdl.handle.net/11693/12922In most compressive sensing problems, 1 norm is used during the signal reconstruction process. In this article, a modified version of the entropy functional is proposed to approximate the 1 norm. The proposed 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 method for compressive sensing applications. Simulation examples with both 1D signals and images are presented. © 2013 Elsevier Inc. All rights reserved.EnglishModified entropy functionalProjection onto convex setsIterative row-action methodsBregman-projectionProximal splittingArticle10.1016/j.dsp.2013.09.010