Publication detail

Artificial Neural Networks For Modelling Wire Antennas

ŠMÍD, P.

Original Title

Artificial Neural Networks For Modelling Wire Antennas

Type

conference paper

Language

English

Original Abstract

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.

Key words in English

Genetic Algorithm, Artificial Neural Network, Dipole Antenna

Authors

ŠMÍD, P.

RIV year

2004

Released

1. 1. 2004

Publisher

Vysoké učení technické v Brně, FEKT

ISBN

80-214-2635-7

Book

STUDENT EEICT 2004 - Proceedings of the 10-th conference

Pages from

155

Pages to

159

Pages count

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"
}