TY  - RPRT
N2  - 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.
M1  - technical_report
A1  - Poli, L.
A1  - Oliveri, G.
A1  - Massa, A.
AV  - public
KW  - Compressive Sensing
KW  -  Inverse Scattering
KW  -  Interval Analysis
KW  -  Evolutionary Optimization
UR  - http://www.eledia.org/students-reports/639/
PB  - University of Trento
Y1  - 2012///
ID  - elediasc12639
TI  - Sparse PEC Scatterers Retrieval by means of a Local Shape Function Bayesian Compressive Sensing Strategy
ER  -