CAD of Stacked Patch Antennas Through Multipurpose Admittance Matrices From FEM and Neural Networks

Córcoles Ortega, Juan, González de Aza, Miguel Ángel and Zapata Ferrer, Juan (2008). CAD of Stacked Patch Antennas Through Multipurpose Admittance Matrices From FEM and Neural Networks. "Microwave and Optical Technology Letters", v. 50 (n. 9); pp. 2411-2416. ISSN 0895-2477. https://doi.org/10.1002/mop.23670.

Description

Title: CAD of Stacked Patch Antennas Through Multipurpose Admittance Matrices From FEM and Neural Networks
Author/s:
  • Córcoles Ortega, Juan
  • González de Aza, Miguel Ángel
  • Zapata Ferrer, Juan
Item Type: Article
Título de Revista/Publicación: Microwave and Optical Technology Letters
Date: September 2008
ISSN: 0895-2477
Volume: 50
Subjects:
Freetext Keywords: computer-aided design, finite element methods, neural networks, optimization algorithms, stacked microstrip antennas
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Electromagnetismo y Teoría de Circuitos [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this work, a novel computer-aided design methodology for probe-fed, cavity-backed, stacked microstrip patch antennas is proposed. The methodology incorporates the rigor of a numerical technique, such as finite element methods, which, in turn, makes use of a newly developed procedure (multipurpose admittance matrices) to carry out a full-wave analysis in a given structure in spite of certain physical shapes and dimensions not yet being established. With the aid of this technique, we form a training set for a neural network, whose output is the desired response of the antenna according to the value of design parameters. Last, taking advantage of this neural network, we perform a global optimization through a genetic algorithm or simulated annealing to obtain a final design. The proposed methodology is validated through a real design whose numerical results are compared with measurements with good agreement.

More information

Item ID: 2562
DC Identifier: https://oa.upm.es/2562/
OAI Identifier: oai:oa.upm.es:2562
DOI: 10.1002/mop.23670
Official URL: http://www3.interscience.wiley.com/journal/1198815...
Deposited by: Memoria Investigacion
Deposited on: 15 Apr 2010 10:47
Last Modified: 20 Apr 2016 12:13
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