Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural methods for antenna array signal processing: a review
Signal Processing
Suitability of different neural networks in daily flow forecasting
Applied Soft Computing
Expert Systems with Applications: An International Journal
A classification technique based on radial basis function neural networks
Advances in Engineering Software
Computers and Electrical Engineering
Multilayer perceptron for prediction of 2006 world cup football game
Advances in Artificial Neural Systems
Orthogonal least squares learning algorithm for radial basis function networks
IEEE Transactions on Neural Networks
A general regression neural network
IEEE Transactions on Neural Networks
Visualizing clusters in artificial neural networks using Morse theory
Advances in Artificial Neural Systems
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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.