Detail výsledku

Genetic Neural Networks for Modeling Dipole Antennas

ŠMÍD, P., RAIDA, Z., LUKEŠ, Z. Genetic Neural Networks for Modeling Dipole Antennas. In Proceeding of the 4th WSEAS International Conference on Applied Informatics and Communications. Puerto De La Cruz, Tenerife: The World Scientific and Egineering Academy and Society, 2004. 5 p. ISBN: 960-8457-06-8.
Typ
článek ve sborníku konference
Jazyk
anglicky
Autoři
Šmíd Petr, Ing., Ph.D.
Raida Zbyněk, prof. Dr. Ing., UREL (FEKT)
Lukeš Zbyněk, Ing., Ph.D.
Abstrakt

The paper deals with original genetic neural networks for modeling wire dipole antennas. A novel approach to learning artificial neural networks (ANN) by genetic algorithms (GA) is described. The goal is to compare the learning abilities of neural antenna models trained by the GA and models trained by gradient algorithms. Developing the original design method based on genetic models of designed electromagnetic structures is the motivation of this work. Two types of ANN, the recurrent Elman ANN and the feed-forward one, are implemented in MATLAB. Results of training abilities are discussed.

Klíčová slova

artificial neural networks, genetic algorithm, wire dipole antenna

Rok
2004
Strany
5
Sborník
Proceeding of the 4th WSEAS International Conference on Applied Informatics and Communications
Vydání
1
Konference
4th WSEAS International Conference on Applied Informatics and Communications
ISBN
960-8457-06-8
Vydavatel
The World Scientific and Egineering Academy and Society
Místo
Puerto De La Cruz, Tenerife
BibTeX 
@inproceedings{BUT12162,
  author="Petr {Šmíd} and Zbyněk {Raida} and Zbyněk {Lukeš}",
  title="Genetic Neural Networks for Modeling Dipole Antennas",
  booktitle="Proceeding of the 4th WSEAS International Conference on Applied Informatics and Communications",
  year="2004",
  number="1",
  pages="5",
  publisher="The World Scientific and Egineering Academy and Society",
  address="Puerto De La Cruz, Tenerife",
  isbn="960-8457-06-8"
}
Pracoviště
Ústav radioelektroniky (UREL)
Nahoru