Automated Modeling of Microwave Structures by Enhanced Neural Networks

Loading...
Thumbnail Image
Date
2006-12
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
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.
Description
Citation
Radioengineering. 2006, vol. 15, č. 4, s. 71-75. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2006/06_04_71_75.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en
Study field
Comittee
Date of acceptance
Defence
Result of defence
Document licence
Creative Commons Attribution 3.0 Unported License
http://creativecommons.org/licenses/by/3.0/
DOI
Collections
Citace PRO