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Research Article

Analysis of Different Performance Parameters of Equilateral Triangular Microstrip Patch Antenna using Artificial Neural Network

Abhishek Tripathi*, Vandana Vikas Thakare, and P. K. Singhal

Department of electronics, Madhav Institute of Technology and Science Gwalior MP, India

*Corresponding Author:
Abhishek Tripathi
Department of electronics, Madhav Institute of Technology and Science Gwalior MP, India
E-mail: [email protected]

Abstract

This paper presents the use of artificial neural network for the estimation of different performance parameters (i.e. Directivity, Radiation Efficiency, Gain and Bandwidth) of a coaxial feed equilateral triangular microstrip patch antenna. Levenberg-Marquardt training algorithms of MLPFFBP-ANN (Multilayer Perceptron feed forward back propagation Artificial Neural Network) has been used to implement the neural network models. The simulated values for training and testing the neural networks are obtained by analysing the equilateral triangular microstrip patch antenna using CST Microwave Studio Software. The results obtained using ANNs are compared with the simulation findings and found quite satisfactory and also it is found that neuro models are not converges using one hidden layer for the calculated training data so more than one one hidden layers are used for training the neural network models. 

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