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Maximum cross section method in the filtering problem for continuous systems with Markovian switching. / Averina, Tatyana A.; Rybakov, Konstantin A.

In: Russian Journal of Numerical Analysis and Mathematical Modelling, Vol. 36, No. 3, 01.06.2021, p. 127-137.

Research output: Contribution to journal › Article › peer-review

Harvard

Averina, TA & Rybakov, KA 2021, 'Maximum cross section method in the filtering problem for continuous systems with Markovian switching', Russian Journal of Numerical Analysis and Mathematical Modelling, vol. 36, no. 3, pp. 127-137. https://doi.org/10.1515/rnam-2021-0011

APA

Averina, T. A., & Rybakov, K. A. (2021). Maximum cross section method in the filtering problem for continuous systems with Markovian switching. Russian Journal of Numerical Analysis and Mathematical Modelling, 36(3), 127-137. https://doi.org/10.1515/rnam-2021-0011

Vancouver

Averina TA, Rybakov KA. Maximum cross section method in the filtering problem for continuous systems with Markovian switching. Russian Journal of Numerical Analysis and Mathematical Modelling. 2021 Jun 1;36(3):127-137. doi: 10.1515/rnam-2021-0011

Author

Averina, Tatyana A. ; Rybakov, Konstantin A. / Maximum cross section method in the filtering problem for continuous systems with Markovian switching. In: Russian Journal of Numerical Analysis and Mathematical Modelling. 2021 ; Vol. 36, No. 3. pp. 127-137.

BibTeX

@article{9adcab32b69f4b5588e1f92c20a208b1,
title = "Maximum cross section method in the filtering problem for continuous systems with Markovian switching",
abstract = "New solution algorithms of optimal filtering problem are proposed for systems with random structure and continuous time. This problem consists in estimating the current state of system based on the results of measurements. The mathematical model of the system includes nonlinear stochastic differential equations whose right-hand side determines the structure of the dynamic system or mode of operation. The right-hand side may vary at random time moments. The number of structures of the system is assumed to be finite and the process of changing the structure to be Markov or conditionally Markov. The state vector of such system consists of two components, namely, a vector with real coordinates and an integer structure number. The law of change of the structure number is determined by the distribution of the random time interval between switchings with a given intensity dependent on the state of system. ",
keywords = "maximum cross section method, Monte Carlo method, particle filter, statistical modelling, Stochastic differential equation with Markovian switching, system with random structure",
author = "Averina, {Tatyana A.} and Rybakov, {Konstantin A.}",
note = "Publisher Copyright: {\textcopyright} 2021 Walter de Gruyter GmbH, Berlin/Boston 2021.",
year = "2021",
month = jun,
day = "1",
doi = "10.1515/rnam-2021-0011",
language = "English",
volume = "36",
pages = "127--137",
journal = "Russian Journal of Numerical Analysis and Mathematical Modelling",
issn = "0927-6467",
publisher = "Walter de Gruyter GmbH",
number = "3",

}

RIS

TY - JOUR

T1 - Maximum cross section method in the filtering problem for continuous systems with Markovian switching

AU - Averina, Tatyana A.

AU - Rybakov, Konstantin A.

N1 - Publisher Copyright: © 2021 Walter de Gruyter GmbH, Berlin/Boston 2021.

PY - 2021/6/1

Y1 - 2021/6/1

N2 - New solution algorithms of optimal filtering problem are proposed for systems with random structure and continuous time. This problem consists in estimating the current state of system based on the results of measurements. The mathematical model of the system includes nonlinear stochastic differential equations whose right-hand side determines the structure of the dynamic system or mode of operation. The right-hand side may vary at random time moments. The number of structures of the system is assumed to be finite and the process of changing the structure to be Markov or conditionally Markov. The state vector of such system consists of two components, namely, a vector with real coordinates and an integer structure number. The law of change of the structure number is determined by the distribution of the random time interval between switchings with a given intensity dependent on the state of system.

AB - New solution algorithms of optimal filtering problem are proposed for systems with random structure and continuous time. This problem consists in estimating the current state of system based on the results of measurements. The mathematical model of the system includes nonlinear stochastic differential equations whose right-hand side determines the structure of the dynamic system or mode of operation. The right-hand side may vary at random time moments. The number of structures of the system is assumed to be finite and the process of changing the structure to be Markov or conditionally Markov. The state vector of such system consists of two components, namely, a vector with real coordinates and an integer structure number. The law of change of the structure number is determined by the distribution of the random time interval between switchings with a given intensity dependent on the state of system.

KW - maximum cross section method

KW - Monte Carlo method

KW - particle filter

KW - statistical modelling

KW - Stochastic differential equation with Markovian switching

KW - system with random structure

UR - http://www.scopus.com/inward/record.url?scp=85108819037&partnerID=8YFLogxK

U2 - 10.1515/rnam-2021-0011

DO - 10.1515/rnam-2021-0011

M3 - Article

AN - SCOPUS:85108819037

VL - 36

SP - 127

EP - 137

JO - Russian Journal of Numerical Analysis and Mathematical Modelling

JF - Russian Journal of Numerical Analysis and Mathematical Modelling

SN - 0927-6467

IS - 3

ER -

ID: 34032494