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On the modeling of linear system input stochastic processes with given accuracy and reliability

Author

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  • Rozora Iryna

    (Department of Applied Statistics, Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv, 60 Volodymyrska Str., 01601Kyiv, Ukraine)

  • Lyzhechko Mariia

    (Department of Applied Statistics, Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv, 60 Volodymyrska Str., 01601Kyiv, Ukraine)

Abstract

The paper is devoted to the model construction for input stochastic processes of a time-invariant linear system with a real-valued square-integrable impulse response function. The processes are considered as Gaussian stochastic processes with discrete spectrum. The response on the system is supposed to be an output process. We obtain the conditions under which the constructed model approximates a Gaussian stochastic process with given accuracy and reliability in the Banach space C⁢([0,1]){C([0,1])}, taking into account the response of the system. For this purpose, the methods and properties of square-Gaussian processes are used.

Suggested Citation

  • Rozora Iryna & Lyzhechko Mariia, 2018. "On the modeling of linear system input stochastic processes with given accuracy and reliability," Monte Carlo Methods and Applications, De Gruyter, vol. 24(2), pages 129-137, June.
  • Handle: RePEc:bpj:mcmeap:v:24:y:2018:i:2:p:129-137:n:5
    DOI: 10.1515/mcma-2018-0011
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    References listed on IDEAS

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    1. Iryna V. Rozora, 2018. "Statistical hypothesis testing for the shape of impulse response function," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(6), pages 1459-1474, March.
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