Detail publikačního výsledku

Neural Networks in Antennas and Microwaves: A Practical Approach

RAIDA, Z.

Originální název

Neural Networks in Antennas and Microwaves: A Practical Approach

Anglický název

Neural Networks in Antennas and Microwaves: A Practical Approach

Druh

Článek recenzovaný mimo WoS a Scopus

Originální abstrakt

Neural networks are electronic systems which can be trained to remember behavior of a modeled structure in given operational points, and which can be used to approximate behavior of the structure out of the training points. These approximation abilities of neural nets are demonstrated on modeling a frequency-selective surface, a microstrip transmission line and a microstrip dipole. Attention is turned to the accuracy and to the efficiency of neural models. The association of neural models and genetic algorithms, which can provide a global design tool, is discussed.

Anglický abstrakt

Neural networks are electronic systems which can be trained to remember behavior of a modeled structure in given operational points, and which can be used to approximate behavior of the structure out of the training points. These approximation abilities of neural nets are demonstrated on modeling a frequency-selective surface, a microstrip transmission line and a microstrip dipole. Attention is turned to the accuracy and to the efficiency of neural models. The association of neural models and genetic algorithms, which can provide a global design tool, is discussed.

Klíčová slova v angličtině

artificial neural networks, genetic algorithms, frequency-selective surfaces, planar transmission lines, microstrip antennas

Autoři

RAIDA, Z.

Vydáno

01.12.2001

ISSN

1210-2512

Periodikum

Radioengineering

Svazek

10

Číslo

4

Stát

Česká republika

Strany od

24

Strany počet

12

BibTex

@article{BUT39632,
  author="Zbyněk {Raida}",
  title="Neural Networks in Antennas and Microwaves: A Practical Approach",
  journal="Radioengineering",
  year="2001",
  volume="10",
  number="4",
  pages="12",
  issn="1210-2512"
}