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Probabilistic properties of non-Gaussian piecewise-linear processes on Poisson flows with independent random values at points of flow. / Ogorodnikov, Vasily A.; Sereseva, Olga V.

в: Russian Journal of Numerical Analysis and Mathematical Modelling, Том 33, № 1, 23.02.2018, стр. 55-64.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

Harvard

Ogorodnikov, VA & Sereseva, OV 2018, 'Probabilistic properties of non-Gaussian piecewise-linear processes on Poisson flows with independent random values at points of flow', Russian Journal of Numerical Analysis and Mathematical Modelling, Том. 33, № 1, стр. 55-64. https://doi.org/10.1515/rnam-2018-0005

APA

Vancouver

Ogorodnikov VA, Sereseva OV. Probabilistic properties of non-Gaussian piecewise-linear processes on Poisson flows with independent random values at points of flow. Russian Journal of Numerical Analysis and Mathematical Modelling. 2018 февр. 23;33(1):55-64. doi: 10.1515/rnam-2018-0005

Author

Ogorodnikov, Vasily A. ; Sereseva, Olga V. / Probabilistic properties of non-Gaussian piecewise-linear processes on Poisson flows with independent random values at points of flow. в: Russian Journal of Numerical Analysis and Mathematical Modelling. 2018 ; Том 33, № 1. стр. 55-64.

BibTeX

@article{70e8f3c655ca4bc09091e30579ee6ae2,
title = "Probabilistic properties of non-Gaussian piecewise-linear processes on Poisson flows with independent random values at points of flow",
abstract = "The paper is focused on study of non-stationary piecewise-linear processes on Poisson point flows with independent identically distributed random variables at support points. An approach to calculate the correlation function of the process on the base of the total probability formula is considered. A general expression for the correlation function of a non-stationary process is obtained. Particular cases are considered. Using the method of direct simulation, it is shown numerically that the correlation function of the process has a point of inflection.",
author = "Ogorodnikov, {Vasily A.} and Sereseva, {Olga V.}",
year = "2018",
month = feb,
day = "23",
doi = "10.1515/rnam-2018-0005",
language = "English",
volume = "33",
pages = "55--64",
journal = "Russian Journal of Numerical Analysis and Mathematical Modelling",
issn = "0927-6467",
publisher = "Walter de Gruyter GmbH",
number = "1",

}

RIS

TY - JOUR

T1 - Probabilistic properties of non-Gaussian piecewise-linear processes on Poisson flows with independent random values at points of flow

AU - Ogorodnikov, Vasily A.

AU - Sereseva, Olga V.

PY - 2018/2/23

Y1 - 2018/2/23

N2 - The paper is focused on study of non-stationary piecewise-linear processes on Poisson point flows with independent identically distributed random variables at support points. An approach to calculate the correlation function of the process on the base of the total probability formula is considered. A general expression for the correlation function of a non-stationary process is obtained. Particular cases are considered. Using the method of direct simulation, it is shown numerically that the correlation function of the process has a point of inflection.

AB - The paper is focused on study of non-stationary piecewise-linear processes on Poisson point flows with independent identically distributed random variables at support points. An approach to calculate the correlation function of the process on the base of the total probability formula is considered. A general expression for the correlation function of a non-stationary process is obtained. Particular cases are considered. Using the method of direct simulation, it is shown numerically that the correlation function of the process has a point of inflection.

UR - http://www.scopus.com/inward/record.url?scp=85042606653&partnerID=8YFLogxK

U2 - 10.1515/rnam-2018-0005

DO - 10.1515/rnam-2018-0005

M3 - Article

AN - SCOPUS:85042606653

VL - 33

SP - 55

EP - 64

JO - Russian Journal of Numerical Analysis and Mathematical Modelling

JF - Russian Journal of Numerical Analysis and Mathematical Modelling

SN - 0927-6467

IS - 1

ER -

ID: 10426970