Bandwidth modeling of U-slot rectangular microstrip antennas with artificial neural networks

In this study, rectangular U-slot microstrip antennas are modeled by an Artificial Neural Network structure and their bandwidth values are calculated with the model. The antenna parameters are taken from in the literature. The experimental results are compared with Artificial Neural Network results. In comparison of the experimental and Artificial Neural Network results, accuracy rates of training and testing were found to be 96.6% and 91.3%, respectively. It is obtained that Artificial Neural Network results are compatible with experimental bandwidth results from the literature. It is shown that possible bandwidth behavior of U-slot rectangular microstrip patch antennas with this Artificial Neural Network model is powerfully estimated.