@techreport{elediasc12668,
            type = {Technical Report},
          author = {L. Poli and G. Oliveri and A. Massa},
           title = {Performance comparison between multi-frequency deterministic and probabilistic approaches},
            year = {2015},
       publisher = {University of Trento},
        abstract = {This report is aimed to show a comparison between the probabilistic inversion methods based on single-task and multi-task Compressive Sensing (CS) strategies recast in a Bayesian framework and a deterministic technique of the state-of-the-art (a conjugate gradient-based method). The results show in particular the better capabilities of the multi-task CS method to take advantage of multi-frequency data when dealing with small-size scatterer in inverse scattering problems. The efficiency and robustness of such a method is validated considering different sparse-scatterer scenarios and different value of signal-to-noise ratio on the data.},
             url = {http://www.eledia.org/students-reports/668/},
        keywords = {Compressive Sensing, Inverse Scattering, Interval Analysis}
}