Abstract
The paper presents the Quasi Newton model of Artificial Neural Network for design of circular microstrip antenna (MSA). In this model, a closed form expression is used for accurate determination of the resonant frequency of circular microstrip patch antenna. The calculated resonant frequency results are in good agreement with the experimental results reported elsewhere. The results show better agreement with the trained and tested data of ANN models. The results are verified by the experimental results to produce accurate ANN models. This presents ANN model practically as an alternative method to the detailed electromagnetic design of circular microstrip antenna.
Highlights
The microstrip antenna (MSA) is an excellent radiator for many applications such as mobile antenna, aircraft and ship antennas, remote sensing, missiles and satellite communications [1]
The results show better agreement with the trained and tested data of Artificial Neural Network (ANN) models
The results are verified by the experimental results to produce accurate ANN models
Summary
The MSA is an excellent radiator for many applications such as mobile antenna, aircraft and ship antennas, remote sensing, missiles and satellite communications [1] It consists of radiating elements (patches) photo etched on the dielectric substrate. Microstrip antennas are low profile conformal configurations They are lightweight, simple and inexpensive, most suited for aerospace and mobile communication. The rectangular and circular patches (Figure 1) are the basic and most commonly used designs in micros- trip antennas. Their designing methods are numerous, yet getting the actual data for developing real prototypes for experiment is found to be difficult. In this paper we have tried to develop the Quasi Newton algorithm for the design of circular patch antennas. ANN models are developed by using NeuroModeler 1.5 tool [5]
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