Recovery of nonlinearly degraded sparse signals through rational optimization

Abstract : We show the benefit which can be drawn from recent global rational optimization methods for the minimization of a regularized criterion. The regularization term is a rational Geman-MacClure like potential, approximating the ℓ0 norm and the fit term is a least-squares criterion suited to a wide class of nonlinear degradation models
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https://hal.archives-ouvertes.fr/hal-01575293
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Marc Castella, Jean-Christophe Pesquet. Recovery of nonlinearly degraded sparse signals through rational optimization. SPARS 2017 - 6th Signal Processing with Adaptive Sparse Structured Representations workshop, Jun 2017, Lisbonne, Portugal. pp.1-2. ⟨hal-01575293⟩

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