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Application of the particle filters for identification of the non-Gaussian systems

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU114705" target="_blank" >RIV/00216305:26220/15:PU114705 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/7145089" target="_blank" >https://ieeexplore.ieee.org/document/7145089</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/CarpathianCC.2015.7145089" target="_blank" >10.1109/CarpathianCC.2015.7145089</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Application of the particle filters for identification of the non-Gaussian systems

  • Original language description

    This paper focuses on application of a particle filter for online identification of non-Gaussian systems. Firstly, the Bayesian inference was described and then the particle filter was defined. The particle filter numerically solves a problem of a recursive Bayesian state estimator. Secondly, the parameters of the linear system and two types of the non-Gaussian systems were estimated by application of the particle filter. The first system was classical linear system. The second system was the linear system with a noise which had a different probability distribution than the Gaussian distribution and the last system was the system with nonlinearity. Thirdly, the parameters of the non-Gaussian systems were estimated with the gradient based method Leveberg-Marquardt. Finally, the results from the particle filter were compared with the results from the gradient based method Levenberg-Marquardt.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • 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 16th International Carpathian Control Conference (ICCC2015)

  • ISBN

    978-1-4799-7369-9

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    282-285

  • Publisher name

    University of Miskolc, Hungary

  • Place of publication

    Szilvásvárad

  • Event location

    Szilvásvárad

  • Event date

    May 27, 2015

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article

    000380488000055