Precise Modeling of Emerging Electronic Structures by Artificial Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00198116" target="_blank" >RIV/68407700:21230/12:00198116 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Precise Modeling of Emerging Electronic Structures by Artificial Neural Networks

Popis výsledku v původním jazyce

Nowadays, there are many emerging electronic structures for which their nonlinear models for computeraided design are necessary, especially for the ones from the areas of nanoelectronics and microwave techniques. However, for such structures, sufficiently accurate analytic models are mostly unavailable. This is partially caused by the fact that the physical principles of the element operation are sometimes not fully clear (especially for quantum devices), and also by bizarre characteristics of some of the elements (typically with irregularities and a hysteresis in parts of characteristics, or by negative differential conductances that are typical for the microwave transistors). In such cases, models based on artificial neural networks are necessary anduseful for these elements. Majority of the elements can be characterized with a single artificial neural network. However, for certain kinds of elements, a cooperation of more artificial neural networks is necessary. This case is describ

Název v anglickém jazyce

Precise Modeling of Emerging Electronic Structures by Artificial Neural Networks

Popis výsledku anglicky

Nowadays, there are many emerging electronic structures for which their nonlinear models for computeraided design are necessary, especially for the ones from the areas of nanoelectronics and microwave techniques. However, for such structures, sufficiently accurate analytic models are mostly unavailable. This is partially caused by the fact that the physical principles of the element operation are sometimes not fully clear (especially for quantum devices), and also by bizarre characteristics of some of the elements (typically with irregularities and a hysteresis in parts of characteristics, or by negative differential conductances that are typical for the microwave transistors). In such cases, models based on artificial neural networks are necessary anduseful for these elements. Majority of the elements can be characterized with a single artificial neural network. However, for certain kinds of elements, a cooperation of more artificial neural networks is necessary. This case is describ

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/GAP102%2F10%2F1614" target="_blank" >GAP102/10/1614: Memristivní, memkapacitivní a meminduktivní systémy: základní výzkum, modelování a simulace</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

World Congress on Engineering and Computer Science 2012

ISBN

978-988-19252-4-4

ISSN

2078-0958

e-ISSN

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Počet stran výsledku

4

Strana od-do

847-850

Název nakladatele

The International Association of Engineers IAENG

Místo vydání

Hong Kong

Místo konání akce

San Francisco

Datum konání akce

24. 10. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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