Detail publikace

Genetic Neural Networks for Modeling Dipole Antennas

ŠMÍD, P., RAIDA, Z., LUKEŠ, Z.

Originální název

Genetic Neural Networks for Modeling Dipole Antennas

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální 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

Autoři

ŠMÍD, P., RAIDA, Z., LUKEŠ, Z.

Rok RIV

2004

Vydáno

1. 12. 2004

Místo

Puerto De La Cruz, Tenerife

ISSN

1109-2750

Periodikum

WSEAS Transactions on Computers

Ročník

6

Číslo

3

Stát

Řecká republika

Strany od

1868

Strany do

1872

Strany počet

5

BibTex

@article{BUT45635,
  author="Petr {Šmíd} and Zbyněk {Raida} and Zbyněk {Lukeš}",
  title="Genetic Neural Networks for Modeling Dipole Antennas",
  journal="WSEAS Transactions on Computers",
  year="2004",
  volume="6",
  number="3",
  pages="5",
  issn="1109-2750"
}