Neural Network Based Resonant Frequency Solver for Rectangular-Shaped Shorting Pin-Loaded Antennas

Abstract

This study presents an artificial neural network (ANN) estimation of the operating frequencies of shorting pin-loaded rectangular microstrip patch antennas. A feed forward back propagation multilayer perceptron neural network structure is applied in the study. The results are compared with the ones in the literature and the FEM based simulation results. The results of the operating frequencies obtained by using this method are in very good agreement with the experimental results presented in the literature. Several antennas are also simulated by a finite element method based solver and these results are also compared with the results of the proposed neural network model. The average error of the lower frequency obtained by this study has a decrement of 2.025% when compared to the FEM based simulation software and for the upper frequency this difference is 6.835%. The effects of permittivity of the antenna, size of the dimensions of the rectangular patch, and the shorting pin position are also evaluated. In the light of the ANN model and the relations obtained two antennas in the same shape are produced and the results of these antennas are presented as well. (c) 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:3025-3028, 2013