Detail publikace

Modeling broadband microwave structures by artificial neural networks

Originální název

Modeling broadband microwave structures by artificial neural networks

Anglický název

Modeling broadband microwave structures by artificial neural networks

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

BibTex


@article{BUT42090,
  author="Zbyněk {Raida} and Zbyněk {Lukeš} and Viktor {Otevřel}",
  title="Modeling broadband microwave structures by artificial neural networks",
  annote="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.",
  chapter="42090",
  journal="Radioengineering",
  number="2",
  volume="13",
  year="2004",
  month="june",
  pages="3",
  type="journal article - other"
}