Compressive Sensing Using the Entropy Functional

Details Compressive Sensing Using the Entropy Functional Compressive Sensing Using the Entropy Functional

2011-01-26

arxiv.org/abs/1101.5079v2

Computer Science

Information Theory

Scientific paper

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.

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