Fractal Antenna Design using Bio-inspired Computing Algorithms

Author(s): Balwinder S. Dhaliwal*, Suman Pattnaik* and Shyam Sundar Pattnaik * .

DOI: 10.2174/9789815136357123010007

Development of ANN Models for the Design of Fractal Antennas

Pp: 84-105 (22)

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* (Excluding Mailing and Handling)

  • * (Excluding Mailing and Handling)

Abstract

SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.

Abstract

In this chapter, the development of ANN models for the design of proposed fractal antennas is explained. The various parameters of the fractal antennas selected for ANN models are described. The ANN models are designed using feed-forward neural networks, namely MLPNN, RBFNN and GRNN. The performance comparison of different ANN models on the basis of different performance measures is also given. The design of ANN ensemble models for fractal antennas is introduced, and different techniques for developing ANN ensemble models are also discussed in this chapter. 

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