Open AccessDesign and Optimization of Microstrip Patch Antenna using Artificial Neural Networks
Author(s) -
Sukhdeep Kaur,
Rajesh Khanna,
Pooja Sahni,
Naveen Kumar
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i1097.0789s19
Subject(s) - computer science , microstrip antenna , artificial neural network , patch antenna , bandwidth (computing) , wideband , microstrip , electronic engineering , software , antenna (radio) , engineering , telecommunications , artificial intelligence , programming language
In this paper a Neural Network model for the design of a Microstrip Patch Antenna for an Ultrawideband frequency range is presented. The reduced ground size is used to enhance bandwidth in proposed design. The results obtained from the proposed method are compared with the results of EM simulation software and are found to be in good agreement. The advantage of the proposed method lies with the fact that the various parameters required for the design of a Microstrip Patch Antenna at a particular frequency of interest can be easily extracted without going into the rigorous time consuming, iterative design procedures using a costly software package. In the paper staircase patch design is considered for ultra-wideband matching of Antenna. The results obtained from artificial neural network when compared with experimental and simulation results, found satisfactory and also it is concluded that Radial Basis Function (RBF) network is more accurate and fast for the proposed design.