ANN characterization of printed reflectarray elements

The design of printed reflectarray antennas (RAs) could be quite complex and computationally expensive, since the need of providing high performances and satisfying requirements that could be also in contrast each other could require the use of a large number of re-radiating advanced element configurations [1,2]. A possible strategy for the RA design could be therefore of carrying it out adopting an evolutionary optimization tool.

[1]  J. Huang,et al.  Microstrip reflectarray , 1991, Antennas and Propagation Society Symposium 1991 Digest.

[2]  D.H. Werner,et al.  Nature-Based Design of Aperiodic Linear Arrays with Broadband Elements Using a Combination of Rapid Neural-Network Estimation Techniques and Genetic Algorithms , 2007, IEEE Antennas and Propagation Magazine.

[3]  F. Grimaccia,et al.  Neural networks and evolutionary algorithm application to complex EM structures modeling , 2009, 2009 International Conference on Electromagnetics in Advanced Applications.

[4]  M. Orefice,et al.  Concentric square ring elements for dual band reflectarray antenna , 2009, 2009 3rd European Conference on Antennas and Propagation.