Adaptive neuro-fuzzy inference system for the input resistance computation of rectangular microstrip antennas with thin and thick substrates


Guney K. , Sarikaya N.

JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS, vol.18, no.1, pp.23-39, 2004 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 18 Issue: 1
  • Publication Date: 2004
  • Doi Number: 10.1163/156939304322749599
  • Title of Journal : JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS
  • Page Numbers: pp.23-39

Abstract

A new method for calculating the input resistance of electrically thin and thick rectangular microstrip patch antennas, based on the adaptive neuro-fuzzy inference system (ANFIS), is presented. The ANFIS has the advantages of expert knowledge of fuzzy inference system and learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the backpropagation algorithm, is used to identify the parameters of ANFIS. The input resistance results obtained by using the new method are in very good agreement with the experimental results available in the literature.