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Description
  • In the recent PSpice-family programs, only a class of five types of the MESFET model is available for a pHEMT representation. In the paper, a way is suggested for modeling pHEMT using a corrective neural network working attached to an updated analytic MESFET model. The accuracy of procedures is assessed by extracting model parameters for a typical TriQuint pHEMT. A sequence of analyses is also performed for determining an optimal structure of the artificial neural network.
  • In the recent PSpice-family programs, only a class of five types of the MESFET model is available for a pHEMT representation. In the paper, a way is suggested for modeling pHEMT using a corrective neural network working attached to an updated analytic MESFET model. The accuracy of procedures is assessed by extracting model parameters for a typical TriQuint pHEMT. A sequence of analyses is also performed for determining an optimal structure of the artificial neural network. (en)
  • In the recent PSpice-family programs, only a class of five types of the MESFET model is available for a pHEMT representation. In the paper, a way is suggested for modeling pHEMT using a corrective neural network working attached to an updated analytic MESFET model. The accuracy of procedures is assessed by extracting model parameters for a typical TriQuint pHEMT. A sequence of analyses is also performed for determining an optimal structure of the artificial neural network. (cs)
Title
  • Improving the Accuracy of PHEMT Models Using Corrective Artifcial Neural Networks
  • Improving the Accuracy of PHEMT Models Using Corrective Artifcial Neural Networks (en)
  • Improving the Accuracy of PHEMT Models Using Corrective Artifcial Neural Networks (cs)
skos:prefLabel
  • Improving the Accuracy of PHEMT Models Using Corrective Artifcial Neural Networks
  • Improving the Accuracy of PHEMT Models Using Corrective Artifcial Neural Networks (en)
  • Improving the Accuracy of PHEMT Models Using Corrective Artifcial Neural Networks (cs)
skos:notation
  • RIV/68407700:21230/07:03132390!RIV08-GA0-21230___
http://linked.open.../vavai/riv/strany
  • 512;515
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/05/0277), Z(MSM6840770014)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 425800
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/07:03132390
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • artificial neural network (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [22C18A1443BC]
http://linked.open...v/mistoKonaniAkce
  • Praha, ČVUT FEL
http://linked.open...i/riv/mistoVydani
  • Cambridge, MA
http://linked.open...i/riv/nazevZdroje
  • PIERS 2007 Prague - Proceeding od Progress In Electromagnetics Research Symposium
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Dobeš, Josef
  • Pospíšil, Ladislav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • The Electromagnetics Academy
https://schema.org/isbn
  • 978-1-934142-02-8
http://localhost/t...ganizacniJednotka
  • 21230
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