DocumentCode
247787
Title
Neural network training schemes for antenna optimization
Author
Linh Ho Manh ; Grimaccia, F. ; Mussetta, M. ; Zich, Riccardo E.
Author_Institution
Dipt. di Energia, Politec. di Milano, Milan, Italy
fYear
2014
fDate
6-11 July 2014
Firstpage
1948
Lastpage
1949
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.
Keywords
electrical engineering computing; microstrip antennas; neural nets; ANN surrogate model; antenna optimization scheme; artificial neural network; degrees of freedom; direct antenna synthesis; electromagnetic field modeling methodology; full-wave analysis; global optimizer; low cost microstrip ring antenna design; low profile microstrip ring antenna design; neural network training schemes; online-trading information; Artificial neural networks; Biological neural networks; Computational modeling; Microstrip antennas; Optimization; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Antennas and Propagation Society International Symposium (APSURSI), 2014 IEEE
Conference_Location
Memphis, TN
ISSN
1522-3965
Print_ISBN
978-1-4799-3538-3
Type
conf
DOI
10.1109/APS.2014.6905301
Filename
6905301
Link To Document