Thanks to the advantage of low profile and low cost, microstrip ring antenna design has been an interesting and challenging issue in modern engineering society. The trade-off among all the degrees of freedom becomes quite complex and direct antenna synthesis by full-wave analysis are often not applicable. In optimization scheme, the associated cost function by computational approach is always expensive and time-consuming. Artificial Neural Network (ANN) has been exploit as a modeling methodology in Electromagnetic field in recent years. In this article, a new approach with the aim of boosting 'online-trading information' between the global optimizer and ANN surrogate model will be discussed.
Neural network training schemes for antenna optimization
GRIMACCIA, FRANCESCO;MUSSETTA, MARCO;ZICH, RICCARDO
2014-01-01
Abstract
Thanks to the advantage of low profile and low cost, microstrip ring antenna design has been an interesting and challenging issue in modern engineering society. The trade-off among all the degrees of freedom becomes quite complex and direct antenna synthesis by full-wave analysis are often not applicable. In optimization scheme, the associated cost function by computational approach is always expensive and time-consuming. Artificial Neural Network (ANN) has been exploit as a modeling methodology in Electromagnetic field in recent years. In this article, a new approach with the aim of boosting 'online-trading information' between the global optimizer and ANN surrogate model will be discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.