Detail publikace

Automated modeling of microwave structures by enhanced neural networks

Petr ŠMÍD, Zbyněk RAIDA

Originální název

Automated modeling of microwave structures by enhanced neural networks

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

The paper describes the methodology of the automated creation of neural models of microwave structures. During the creation process, artificial neural networks are trained using the combination of the particle swarm optimization and the quasi-Newton method to avoid critical training problems of the conventional neural nets. In the paper, neural networks are used to approximate the behavior of a planar microwave filter (moment method, Zeland IE3D). In order to evaluate the efficiency of neural modeling, global optimizations are performed using numerical models and neural ones. Both approaches are compared from the viewpoint of CPU-time demands and the accuracy. Considering conclusions, methodological recommendations for including neural networks to the microwave design are formulated

Klíčová slova

Feed-forward neural network, recurrent neural net¬work, particle swarm optimization

Autoři

Petr ŠMÍD, Zbyněk RAIDA

Rok RIV

2006

Vydáno

1. 12. 2006

ISSN

1210-2512

Periodikum

Radioengineering

Ročník

15

Číslo

4

Stát

Česká republika

Strany od

71

Strany do

75

Strany počet

5

BibTex

@article{BUT43724,
  author="Petr {Šmíd} and Zbyněk {Raida}",
  title="Automated modeling of microwave structures by enhanced neural networks",
  journal="Radioengineering",
  year="2006",
  volume="15",
  number="4",
  pages="5",
  issn="1210-2512"
}