Publication detail

Enhanced neural modeling of planar antennas and filters

Petr Šmíd, Zbyněk Raida, Jiří Horák

Original Title

Enhanced neural modeling of planar antennas and filters

English Title

Enhanced neural modeling of planar antennas and filters

Type

conference paper

Language

en

Original Abstract

The paper deals with an enhanced neural modeling algorithm based on incorporation of both, global optimization method and local one. Proposed algorithm depresses disadvantages of classical neural modeling. A neural model of the low-pass filter is trained to behave as a numerical one, which is analyzed in Zeland IE3D. Both, the neural model and the numerical one are optimized using particle swarm optimization method (PSO). Finally, the results of optimization are compared.

English abstract

The paper deals with an enhanced neural modeling algorithm based on incorporation of both, global optimization method and local one. Proposed algorithm depresses disadvantages of classical neural modeling. A neural model of the low-pass filter is trained to behave as a numerical one, which is analyzed in Zeland IE3D. Both, the neural model and the numerical one are optimized using particle swarm optimization method (PSO). Finally, the results of optimization are compared.

Keywords

Artificial neural networks, planar microwave structures, pso.

RIV year

2006

Released

04.10.2006

Publisher

Antenna Centre of Excellence

Location

Nice (Francie)

ISBN

9-2909-2937-5

Book

Proceedings of the European Conference on Antennas and Propagation EuCAP 2006

Pages from

448

Pages to

451

Pages count

4

BibTex


@inproceedings{BUT24886,
  author="Zbyněk {Raida} and Petr {Šmíd} and Jiří {Horák}",
  title="Enhanced neural modeling of planar antennas and filters",
  annote="The paper deals with an enhanced neural modeling algorithm based on incorporation of both, global optimization method and local one. Proposed algorithm depresses disadvantages of classical neural modeling. A neural model of the low-pass filter is trained to behave as a numerical one, which is analyzed in Zeland IE3D. Both, the neural model and the numerical one are optimized using particle swarm optimization method (PSO). Finally, the results of optimization are compared.
",
  address="Antenna Centre of Excellence",
  booktitle="Proceedings of the European Conference on Antennas and Propagation EuCAP 2006",
  chapter="24886",
  institution="Antenna Centre of Excellence",
  year="2006",
  month="october",
  pages="448",
  publisher="Antenna Centre of Excellence",
  type="conference paper"
}