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RAIDA, Z., LUKEŠ, Z., OTEVŘEL, V.
Original Title
Modeling broadband microwave structures by artificial neural networks
Type
journal article - other
Language
English
Original Abstract
The paper describes the exploitation of feed-forward neural networks and recurrent neural networks for replacing full-wave numerical models of microwave structures in complex microwave design tools. Building a neural model, attention is turned to the modeling accuracy and to the efficiency of building a model. Dealing with the accuracy, we describe a method of increasing it by successive completing a training set. Neural models are mutually compared in order to highlight their advantages and disadvantages. As a reference model for comparisons, approximations based on standard cubic splines are used. Neural models are used to replace both the time-domain numeric models and the frequency-domain ones.
Keywords
Artificial neural networks, frequency-domain finite elements, time-domain method of moments, wire antennas, microwave transmission lines.
Authors
RIV year
2004
Released
1. 6. 2004
ISBN
1210-2512
Periodical
Radioengineering
Year of study
13
Number
2
State
Czech Republic
Pages from
3
Pages to
11
Pages count
9
BibTex
@article{BUT42090, author="Zbyněk {Raida} and Zbyněk {Lukeš} and Viktor {Otevřel}", title="Modeling broadband microwave structures by artificial neural networks", journal="Radioengineering", year="2004", volume="13", number="2", pages="9", issn="1210-2512" }