Efficient Computation of Resonant Frequency of Rectangular Microstrip Antenna using a Neural Network Model with Two Stage Training

Artificial neural networks (ANNs) with two stage training have been proposed for efficient computation of resonant frequency of rectangular microstrip antenna. In the proposed approach in first stage the ANN model trained with empirical relation of resonant frequency with structural and substrate parameters of antenna then in second stage the model has been trained with the actual experimental data. The proposed approach has been validated using experimental published data and compared with results of other models published in different research papers. The result shows that the proposed approach is more accurate than the models developed using experimental data only. The results of the two stage training are in very good agreement with the measurements, and better accuracy than other ANN models developed using experimental data only.