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Petr ŠMÍD, Zbyněk RAIDA
Original Title
Automated modeling of microwave structures by enhanced neural networks
Type
journal article - other
Language
English
Original 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
Keywords
Feed-forward neural network, recurrent neural net¬work, particle swarm optimization
Authors
RIV year
2006
Released
1. 12. 2006
ISBN
1210-2512
Periodical
Radioengineering
Year of study
15
Number
4
State
Czech Republic
Pages from
71
Pages to
75
Pages count
5
BibTex
@article{BUT43724, author="Petr {Šmíd} and Zbyněk {Raida}", title="Automated modeling of microwave structures by enhanced neural networks", journal="Radioengineering", year="2006", volume="15", number="4", pages="5", issn="1210-2512" }