Performance investigations of S-shaped RMSA using multilayer perceptron neural network for S-band applications

Mohammad Aneesh; Ashish Singh; Kumari Kamakshi; Jamshed Aslam Ansari

doi:10.3103/S073527271908003X

Authors

Mohammad Aneesh Veer Bahadur Singh Purvanchal University, Jaunpur, India
Ashish Singh NMAM Institute of Technology, Nitte, India https://orcid.org/0000-0003-4099-2780
Kumari Kamakshi Institute of Management Studies, Ghaziabad, India
Jamshed Aslam Ansari University of Allahabad, India

DOI:

https://doi.org/10.3103/S073527271908003X

Keywords:

artificial neural network, Levenberg-Marquardt, rectangular microstrip patch antenna, wideband operation

Abstract

In this article an S-shaped rectangular microstrip patch antenna (RMSA) is investigated for S-band applications using artificial neural network (ANN). The authors have done the parametric study of different radiating structures to obtain S-shaped RMSA. The size of inserted notches on the radiating patch for achieving wideband operation is computed through multilayer perceptron artificial neural network (MLP-ANN) over a desired range of its performance effecting parameters such as frequency, gain, directivity, antenna efficiency, and radiation efficiency. MLP-ANN model is trained and tested with seven different algorithms. The research found that Levenberg-Marquardt (LM) training algorithm takes less computational time with better accuracy for computation of notches size on radiating patch over a priory defined performance parameters. To verify the work, a prototype of S-shaped RMSA is physically fabricated on foam substrate and tested experimentally. The experimental results are in good agreement with the simulated results that are produced with ANN.

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