Open AccessOptimal design of frequency selective surfaces with fractal motifs
Author(s) -
Silva Marcelo Ribeiro da,
Nóbrega Clarissa de Lucena,
Silva Paulo Henrique da F.,
D'Assunção Adaildo Gomes
Publication year - 2014
Publication title -
iet microwaves, antennas and propagation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.555
H-Index - 69
eISSN - 1751-8733
pISSN - 1751-8725
DOI - 10.1049/iet-map.2013.0462
Subject(s) - fractal , particle swarm optimization , algorithm , computer science , artificial neural network , computation , parametric statistics , bandwidth (computing) , genetic algorithm , mathematical optimization , mathematics , artificial intelligence , telecommunications , mathematical analysis , statistics
An alternative electromagnetic (EM) optimisation technique for the optimal design of frequency selective surfaces (FSSs) with fractal motifs is described. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated with FSS parametric full‐wave analysis. In an application example, a fast and accurate multilayer perceptrons model of a FSS band‐stop spatial filter with a Vicsek fractal motif is developed. This neural network model is used for repetitive cost function computations in population‐based search algorithm simulations. A bees algorithm, continuous genetic algorithm and particle swarm optimisation are used for FSS optimisation with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of numerical convergence. Consistent results are presented for a second‐pass of designed FSS prototype with Vicsek fractal elements.