Detail publikace

Artificial Neural Networks For Modelling Wire Antennas

ŠMÍD, P.

Originální název

Artificial Neural Networks For Modelling Wire Antennas

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The paper describes an approach to learning artificial neural networks (ANN) with the genetic algorithm (GA). The goal is modeling the wire dipole by ANN. The arm dipole length, frequency and input impedance are the training parameters for learning the ANN. Two types of ANN were selected for mentioned problem: the recurrent Elman ANN and the feed-forward one. Neural networks are implemented in MATLAB. Results of training abilities are discussed.

Klíčová slova v angličtině

Genetic Algorithm, Artificial Neural Network, Dipole Antenna

Autoři

ŠMÍD, P.

Rok RIV

2004

Vydáno

1. 1. 2004

Nakladatel

Vysoké učení technické v Brně, FEKT

ISBN

80-214-2635-7

Kniha

STUDENT EEICT 2004 - Proceedings of the 10-th conference

Strany od

155

Strany do

159

Strany počet

5

BibTex

@inproceedings{BUT11391,
  author="Petr {Šmíd}",
  title="Artificial Neural Networks For Modelling Wire Antennas",
  booktitle="STUDENT EEICT 2004 - Proceedings of the 10-th conference",
  year="2004",
  pages="5",
  publisher="Vysoké učení technické v Brně, FEKT",
  isbn="80-214-2635-7"
}