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Neurospectral computation for the resonant characteristics of microstrip patch antenna printed on uniaxially anisotropic substrates

Published online by Cambridge University Press:  10 February 2016

Lamia Barkat
Affiliation:
Electronics Department, University of Batna, 05000 Batna, Algeria
Sami Bedra*
Affiliation:
Industrial Engineering Department, University of Khenchela, 40004 Khenchela, Algeria. Phone: +21333857526
Tarek Fortaki
Affiliation:
Electronics Department, University of Batna, 05000 Batna, Algeria
Randa Bedra
Affiliation:
Electronics Department, University of Batna, 05000 Batna, Algeria
*
Corresponding author: S. Bedra Email: bedra_sami@yahoo.fr

Abstract

Modeling and design of rectangular microstrip patch printed on isotropic or anisotropic substrate are accomplished in this paper. The use of spectral domain method in conjunction with artificial neural networks (ANNs) to compute the resonant characteristics of rectangular microstrip patch printed on isotropic or anisotropic substrates. The moment method implemented in the spectral domain offers good accurateness, but its computational cost is high owing to the evaluation of the slowly decaying integrals and the iterative nature of the solution process. The paper introduces the electromagnetic knowledge combined with ANN in the analysis of rectangular microstrip antenna on uniaxially anisotropic substrate to reduce the complexity of the spectral domain method and to minimize the CPU time necessary to obtain the numerical results. The numerical comparison between neurospectral and conventional moment methods shows significant improvements in time convergence and computational cost. Hence, the use of neurospectral approach presented here as a promising fast technique in the design of microstrip antennas.

Type
Research Papers
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2016 

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References

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