Design and feed position estimation for circular microstrip antenna based on neural network model

Author

Vilovic, Ivan ; Burum, Niksa

Author_Institution

Dept. of Electr. Eng. & Comput., Univ. of Dubrovnik, Dubrovnik, Croatia

fYear

2012

fDate

26-30 March 2012

Firstpage

3614

Lastpage

3617

Abstract

In this paper a design and feed position determination for circular microstrip antenna based on neural network models are presented. Multilayer perceptron (MLP) is developed for antenna design. The physical and effective radius, as well as, directivity is obtained by MLP neural network. Radial basis function (RBF) neural network is used for feed position estimation. The obtained results are showed good matching with experimentally obtained results.

Keywords

antenna feeds; electrical engineering computing; microstrip antennas; multilayer perceptrons; radial basis function networks; MLP; RBF; antenna design; circular microstrip antenna; effective radius; feed position estimation; multilayer perceptron; neural network models; physical radius; radial basis function; Antenna feeds; Biological neural networks; Impedance; Microstrip; Microstrip antennas; Neurons; Training; circular microstrip antenna; effective radius; feed position; input impedance; neural network; phyisical radius;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation (EUCAP), 2012 6th European Conference on

Conference_Location

Prague

Print_ISBN

978-1-4577-0918-0

Electronic_ISBN

978-1-4577-0919-7

Type

conf

DOI

10.1109/EuCAP.2012.6206281

Filename

6206281