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Artificial bee colony algorithm for small signal model parameter extraction of MESFET

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86075425" target="_blank" >RIV/61989100:27240/10:86075425 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Artificial bee colony algorithm for small signal model parameter extraction of MESFET

  • Original language description

    This paper presents an application of swarm intelligence technique namely artificial bee colony (ABC) to extract the small signal equivalent circuit model parameters of GaAs metal extended semiconductor field effect transistor (MESFET) device and compares its performance with particle swarm optimization (PSO) algorithm. Parameter extraction in MESFET process involves minimizing the error, which is measured as the difference between modeled and measured S parameter over a broad frequency range. This error surface is viewed as a multi-modal error surface and robust optimization algorithms are required to solve this kind of problem.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2010

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

  • ISSN

    0952-1976

  • e-ISSN

  • Volume of the periodical

    23

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    6

  • Pages from-to

  • UT code for WoS article

    000279060300006

  • EID of the result in the Scopus database