This paper deals with analytical modelling of microstrip patch antenna (MSA) by means of artificial neural network (ANN) using\nleast mean square (LMS) and recursive least square (RLS) algorithms. Our contribution in this work is twofold.We initially provide\na tutorial-like exposition for the design aspects ofMSAand for the analytical framework of the two algorithmswhile our second aim\nis to take advantage of high nonlinearity of MSA to compare the effectiveness of LMS and that of RLS algorithms. We investigate\nthe two algorithms by using gradient decent optimization in the context of radial basis function (RBF) of ANN. The proposed\nanalysis is based on both static and adaptive spread factor. We model the forward side or synthesis of MSA by means of worked\nexamples and simulations. Contour plots, 3D depictions, and Tableau presentations provide a comprehensive comparison of the\ntwo algorithms. Our findings point to higher accuracies in approximation for synthesis of MSA using RLS algorithm as compared\nwith that of LMS approach; however the computational complexity increases in the former case.
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