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 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">Infocommunications and Radio Technologies</journal-id>
   <journal-title-group>
    <journal-title xml:lang="en">Infocommunications and Radio Technologies</journal-title>
    <trans-title-group xml:lang="ru">
     <trans-title>ИНФОКОММУНИКАЦИОННЫЕ И РАДИОЭЛЕКТРОННЫЕ ТЕХНОЛОГИИ</trans-title>
    </trans-title-group>
   </journal-title-group>
   <issn publication-format="print">2587-9936</issn>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="publisher-id">53200</article-id>
   <article-id pub-id-type="doi">10.29039/2587-9936.2022.05.1.03</article-id>
   <article-categories>
    <subj-group subj-group-type="toc-heading" xml:lang="ru">
     <subject>Электроника, фотоника, приборостроение и связь (2.2)</subject>
    </subj-group>
    <subj-group subj-group-type="toc-heading" xml:lang="en">
     <subject>ELECTRONICS, PHOTONICS, INSTRUMENTATION AND COMMUNICATIONS (2.2)</subject>
    </subj-group>
    <subj-group>
     <subject>Электроника, фотоника, приборостроение и связь (2.2)</subject>
    </subj-group>
   </article-categories>
   <title-group>
    <article-title xml:lang="en">Application of Neural Networks in the Construction of Nonlinear Models of Field-Effect Transistors</article-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Применение нейронных сетей при построении нелинейных моделей полевых транзисторов</trans-title>
    </trans-title-group>
   </title-group>
   <contrib-group content-type="authors">
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Богданов</surname>
       <given-names>Сергей Александрович</given-names>
      </name>
      <name xml:lang="en">
       <surname>Bogdanov</surname>
       <given-names>Sergey Aleksandrovich</given-names>
      </name>
     </name-alternatives>
     <email>bogdanov_sa@mail.ru</email>
     <bio xml:lang="ru">
      <p>кандидат технических наук;</p>
     </bio>
     <bio xml:lang="en">
      <p>candidate of technical sciences;</p>
     </bio>
     <xref ref-type="aff" rid="aff-1"/>
    </contrib>
   </contrib-group>
   <aff-alternatives id="aff-1">
    <aff>
     <institution xml:lang="ru">АО «НПП “Исток” имени А. И. Шокина»</institution>
     <city>Фрязино</city>
     <country>Россия</country>
    </aff>
    <aff>
     <institution xml:lang="en">Scientific and production enterprise “Istok” n. a. A. I. Shokin</institution>
     <city>Fryazino</city>
     <country>Russian Federation</country>
    </aff>
   </aff-alternatives>
   <pub-date publication-format="print" date-type="pub" iso-8601-date="2022-03-25T20:22:29+03:00">
    <day>25</day>
    <month>03</month>
    <year>2022</year>
   </pub-date>
   <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2022-03-25T20:22:29+03:00">
    <day>25</day>
    <month>03</month>
    <year>2022</year>
   </pub-date>
   <volume>5</volume>
   <issue>1</issue>
   <fpage>45</fpage>
   <lpage>53</lpage>
   <history>
    <date date-type="received" iso-8601-date="2022-03-20T20:22:29+03:00">
     <day>20</day>
     <month>03</month>
     <year>2022</year>
    </date>
    <date date-type="accepted" iso-8601-date="2022-06-05T00:00:00+03:00">
     <day>05</day>
     <month>06</month>
     <year>2022</year>
    </date>
   </history>
   <self-uri xlink:href="https://rusjbpc.ru/en/nauka/article/53200/view">https://rusjbpc.ru/en/nauka/article/53200/view</self-uri>
   <abstract xml:lang="ru">
    <p>На основе математического аппарата теории искусственных нейронных сетей разработана нелинейная модель полевого транзистора, особенностью которой является возможность обучения нейронных сетей, используемых для аппроксимации вольтамперной характеристики и емкостей затвор-сток и затвор-исток нелинейной модели транзистора встроенными в популярные СВЧ САПР алгоритмами оптимизации. Это позволяет использовать известные преимущества нейронных сетей в задачах аппроксимации функций для повышения достоверности результатов нелинейного моделирования СВЧ-устройств на основе полевых транзисторов.</p>
   </abstract>
   <trans-abstract xml:lang="en">
    <p>The nonlinear model of a field-effect transistor based on the mathematical apparatus of the theory of artificial neural networks was developed. The main feature of this model is the possibility of training neural networks used to approximate the current-voltage characteristic and the gate-drain and gate-source capacitances of a nonlinear transistor model by using optimization algorithms built into popular microwave CAD systems. This makes it possible to use the well-known advantages of neural networks in the problems of function approximation to increase the reliability of the results of non-linear modeling of microwave devices based on field-effect transistors.</p>
   </trans-abstract>
   <kwd-group xml:lang="ru">
    <kwd>нелинейная модель полевого транзистора</kwd>
    <kwd>искусственные нейронные сети</kwd>
    <kwd>радиальная базисная сеть</kwd>
    <kwd>функция активации</kwd>
    <kwd>«SoftPlus»</kwd>
   </kwd-group>
   <kwd-group xml:lang="en">
    <kwd>nonlinear model of a field-effect transistor; artificial neural networks; radial basic network; activation function; SoftPlus</kwd>
   </kwd-group>
  </article-meta>
 </front>
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