relation: http://www.eledia.org/students-reports/639/
title: Sparse PEC Scatterers Retrieval by means of a Local Shape Function Bayesian Compressive Sensing Strategy
creator: Poli, L.
creator: Oliveri, G.
creator: Massa, A.
subject: M CS Compressive Sensing
subject: M EA Evolutionary Algorithms
description: This report proposes an analysis on the dependence of the performances of the the local shape function multi-task Bayesian compressive sensing method on the number of scattering data when various measurement setups different from the optimal one have been considered, in order to show the effectiveness of the compressive sensing-based methodology when dealing with few data. Comparison with the single-task Bayesian compressive sensing implementation are also proposed.
publisher: University of Trento
date: 2012
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/639/1/Sparse%20PEC%20Scatterers%20Retrieval%20by%20means%20of%20a%20Local%20Shape%20Function%20Bayesian%20Compressive%20Sensing%20Strategy.pdf
identifier:   Poli, L. and Oliveri, G. and Massa, A.  (2012) Sparse PEC Scatterers Retrieval by means of a Local Shape Function Bayesian Compressive Sensing Strategy.  Technical Report. University of Trento.