Selecting an Optimal Structure of Artificial Neural Networks for Characterizing RF Semiconductor Devices
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00171283" target="_blank" >RIV/68407700:21230/10:00171283 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Selecting an Optimal Structure of Artificial Neural Networks for Characterizing RF Semiconductor Devices
Original language description
In the paper, a method is suggested for modeling miscellaneous RF semiconductor devices by exclusive neural networks or by corrective neural networks working attached to a modified analytic model. An accuracy of the proposed modification of the analyticmodel is assessed by extracting model parameters of the AlGaAs/InGaAs/GaAs pHEMT. An accuracy of procedures with neural networks is generally assessed by extracting their parameters in static and dynamic domains. An approximation of the AlGaAs/InGaAs/GaAs pHEMT output characteristics is carried out by means of both exclusive and corrective artificial neural networks. A systematic sequence of analyses is also performed for examining an optimal structure of the artificial neural network from the point ofview its structure and complexity. The tests have been performed on both five- and four-layer artificial neural networks that serve for modeling a P-channel JFET and for the AlGaAs/InGaAs/GaAs pHEMT.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP102%2F10%2F1614" target="_blank" >GAP102/10/1614: Memristive, memcapacitative, and meminductive systems: basic research, modeling, and simulation</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 53rd IEEE International Midwest Symposium on Circuits and Systems
ISBN
978-1-4244-7773-9
ISSN
1548-3746
e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
Seattle, Washington
Event date
Aug 1, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000287099800290