Resonant Frequency Analysis of Coaxial Feed Equilateral Triangular Microstrip Antenna Using Neural Network

In this paper a novel technique is proposed for the estimation of resonant frequency of coaxial feed equilateral triangular microstrip patch antenna. The major advantage of the proposed approach is that, after proper training, proposed neural model completely bypasses the repeated use of complex i terative process for calculation of resonant frequency, thus resulting in an extremely fast solution with high accuracy. The Levenberg Marquardt training algorithm of MLPFFBP-ANN (Multilayer Perceptron feed forward back propagation Artificial Neural Network) and RBF-ANN (Radial basis function Artificial Neural Network) have been used to implement the neural network model. For this purpose, the training and validation data is obtained by analysing the equilateral triangular microstrip antenna using Computer Simulation Technology Microwave Studio (CS T MWS) Software. The results obtained using ANN models are found in agreement with the simulation findings, and also it is concluded that RBF network is more accurate and fast as compared to MLPFFBP network.