Table of Contents
Advances in Artificial Neural Systems
Volume 2013 (2013), Article ID 560969, 7 pages
http://dx.doi.org/10.1155/2013/560969
Research Article

Artificial Neural Network Analysis of Sierpinski Gasket Fractal Antenna: A Low Cost Alternative to Experimentation

1Guru Nanak Dev Engineering College, Ludhiana, Punjab 141006, India
2National Institute of Technical Teachers' Training and Research, Chandigarh 160019, India

Received 29 June 2013; Accepted 9 September 2013

Academic Editor: Ozgur Kisi

Copyright © 2013 Balwinder S. Dhaliwal and Shyam S. Pattnaik. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Artificial neural networks due to their general-purpose nature are used to solve problems in diverse fields. Artificial neural networks (ANNs) are very useful for fractal antenna analysis as the development of mathematical models of such antennas is very difficult due to complex shapes and geometries. As such empirical approach doing experiments is costly and time consuming, in this paper, application of artificial neural networks analysis is presented taking the Sierpinski gasket fractal antenna as an example. The performance of three different types of networks is evaluated and the best network for this type of applications has been proposed. The comparison of ANN results with experimental results validates that this technique is an alternative to experimental analysis. This low cost method of antenna analysis will be very useful to understand various aspects of fractal antennas.