@mastersthesis{elediasc1296,
            year = {2012},
           title = {Synthesis of Sparse Complex Arrays by BCS},
          author = {N. Mbonimba},
          school = {University of Trento},
             url = {http://www.eledia.org/students-reports/96/},
        keywords = {DCM},
        abstract = {The design of sparse arrays can be carried out with several techniques, including optimization approaches (GA, SA, PSO) and matrix-pencil techniques. Recently, the exploitation of Bayesian Compressive Sampling has been proposed as a powerful tool to design sparse arrays with arbitrary patterns. Such an approach essentially exploits the capability of BCS to reliably reconstruct arbitrary functions with a sub-Nyquist sampling. However, such a technique has been applied only to symmetric and real linear arrays, which represent only a specific case to be taken into account in practical scenarios. As a consequences, the objective of the activity will be that of analyzing the performances of the above methodology when dealing with linear complex and asymmetric patterns.}
}