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Compressive Sensing Using the Entropy Functional

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 نشر من قبل Kivanc Kose
 تاريخ النشر 2011
  مجال البحث الهندسة المعلوماتية
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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 Bregmans row action D-projection method for compressive sensing applications. Simulation examples are presented.



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