Automated Modeling of Microwave Structures by Enhanced Neural Networks

The paper describes the methodology of the automated creation of neural models of microwave structures. During the creation process, artificial neural networks are trained using the combination of the particle swarm optimization and the quasi-Newton method to avoid critical training problems of the...

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Main Authors: Z. Raida, P. Smid
Format: Article
Language:English
Published: Spolecnost pro radioelektronicke inzenyrstvi 2006-12-01
Series:Radioengineering
Online Access:http://www.radioeng.cz/fulltexts/2006/06_04_71_75.pdf
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spelling doaj-6e90326e557e488aa8b1fa28881e5bf72020-11-24T21:34:20ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122006-12-011547175Automated Modeling of Microwave Structures by Enhanced Neural NetworksZ. RaidaP. SmidThe paper describes the methodology of the automated creation of neural models of microwave structures. During the creation process, artificial neural networks are trained using the combination of the particle swarm optimization and the quasi-Newton method to avoid critical training problems of the conventional neural nets. In the paper, neural networks are used to approximate the behavior of a planar microwave filter (moment method, Zeland IE3D). In order to evaluate the efficiency of neural modeling, global optimizations are performed using numerical models and neural ones. Both approaches are compared from the viewpoint of CPU-time demands and the accuracy. Considering conclusions, methodological recommendations for including neural networks to the microwave design are formulated.www.radioeng.cz/fulltexts/2006/06_04_71_75.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Z. Raida
P. Smid
spellingShingle Z. Raida
P. Smid
Automated Modeling of Microwave Structures by Enhanced Neural Networks
Radioengineering
author_facet Z. Raida
P. Smid
author_sort Z. Raida
title Automated Modeling of Microwave Structures by Enhanced Neural Networks
title_short Automated Modeling of Microwave Structures by Enhanced Neural Networks
title_full Automated Modeling of Microwave Structures by Enhanced Neural Networks
title_fullStr Automated Modeling of Microwave Structures by Enhanced Neural Networks
title_full_unstemmed Automated Modeling of Microwave Structures by Enhanced Neural Networks
title_sort automated modeling of microwave structures by enhanced neural networks
publisher Spolecnost pro radioelektronicke inzenyrstvi
series Radioengineering
issn 1210-2512
publishDate 2006-12-01
description The paper describes the methodology of the automated creation of neural models of microwave structures. During the creation process, artificial neural networks are trained using the combination of the particle swarm optimization and the quasi-Newton method to avoid critical training problems of the conventional neural nets. In the paper, neural networks are used to approximate the behavior of a planar microwave filter (moment method, Zeland IE3D). In order to evaluate the efficiency of neural modeling, global optimizations are performed using numerical models and neural ones. Both approaches are compared from the viewpoint of CPU-time demands and the accuracy. Considering conclusions, methodological recommendations for including neural networks to the microwave design are formulated.
url http://www.radioeng.cz/fulltexts/2006/06_04_71_75.pdf
work_keys_str_mv AT zraida automatedmodelingofmicrowavestructuresbyenhancedneuralnetworks
AT psmid automatedmodelingofmicrowavestructuresbyenhancedneuralnetworks
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