Cramer-Rao Bound for a Sparse Complex Model

Abstract : Complex-valued data play a prominent role in a number of signal and image processing applications. The aim of this paper is to establish some theoretical results concerning the Cramer-Rao bound for estimating a spars complex-valued vector. Instead of considering a countable dictionary of vectors, we address the more challenging case of an uncountable set of vectors parameterized by a real variable. We also present a proximal forward-backward algorithm to minimize an l0 penalized cost, which allows us to approach the derived bounds. These results are illustrated on a spectrum analysis problem in the case of irregularly sampled observations.
Contributeur : Emilie Chouzenoux <>
Soumis le : mercredi 7 mai 2014 - 18:34:25
Dernière modification le : mercredi 15 avril 2015 - 16:08:21
Document(s) archivé(s) le : jeudi 7 août 2014 - 12:05:32


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  • HAL Id : hal-00988369, version 1


Anisia Florescu, Emilie Chouzenoux, Jean-Christophe Pesquet, Silviu Ciochina. Cramer-Rao Bound for a Sparse Complex Model. 4p. 2014. <hal-00988369>



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