Standard

Statistical modeling of random processes with invariants. / Averina, Tatiana; Karachanskaya, Elena; Rybakov, Konstantin.

Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 34-37 8109832.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Averina, T, Karachanskaya, E & Rybakov, K 2017, Statistical modeling of random processes with invariants. in Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017., 8109832, Institute of Electrical and Electronics Engineers Inc., pp. 34-37, 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017, Novosibirsk, Russian Federation, 18.09.2017. https://doi.org/10.1109/SIBIRCON.2017.8109832

APA

Averina, T., Karachanskaya, E., & Rybakov, K. (2017). Statistical modeling of random processes with invariants. In Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 (pp. 34-37). [8109832] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIBIRCON.2017.8109832

Vancouver

Averina T, Karachanskaya E, Rybakov K. Statistical modeling of random processes with invariants. In Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 34-37. 8109832 doi: 10.1109/SIBIRCON.2017.8109832

Author

Averina, Tatiana ; Karachanskaya, Elena ; Rybakov, Konstantin. / Statistical modeling of random processes with invariants. Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 34-37

BibTeX

@inproceedings{300f5108badb4c36946c79f99bda271d,
title = "Statistical modeling of random processes with invariants",
abstract = "The main goal of this paper is to study and to test the numerical methods for stochastic differential equations with solutions on a given smooth manifold. Second-order cylindrical surfaces such as elliptic, hyperbolic, and parabolic cylinders are chosen as manifolds in three-dimensional space provided that the phase space is two-dimensional space. The classes of stochastic differential equations are formed for the considered manifolds and linear equations with multiplicative noise that are the particular case of these classes are concerned. The numerical methods accuracy as the mean distance between solutions and the given smooth manifold is estimated. The comparative analysis of the results obtained by using the different numerical methods is given.",
keywords = "First integral, Invariant, Numerical method, Random process, Stochastic differential equation",
author = "Tatiana Averina and Elena Karachanskaya and Konstantin Rybakov",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 ; Conference date: 18-09-2017 Through 22-09-2017",
year = "2017",
month = nov,
day = "14",
doi = "10.1109/SIBIRCON.2017.8109832",
language = "English",
pages = "34--37",
booktitle = "Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

RIS

TY - GEN

T1 - Statistical modeling of random processes with invariants

AU - Averina, Tatiana

AU - Karachanskaya, Elena

AU - Rybakov, Konstantin

N1 - Publisher Copyright: © 2017 IEEE.

PY - 2017/11/14

Y1 - 2017/11/14

N2 - The main goal of this paper is to study and to test the numerical methods for stochastic differential equations with solutions on a given smooth manifold. Second-order cylindrical surfaces such as elliptic, hyperbolic, and parabolic cylinders are chosen as manifolds in three-dimensional space provided that the phase space is two-dimensional space. The classes of stochastic differential equations are formed for the considered manifolds and linear equations with multiplicative noise that are the particular case of these classes are concerned. The numerical methods accuracy as the mean distance between solutions and the given smooth manifold is estimated. The comparative analysis of the results obtained by using the different numerical methods is given.

AB - The main goal of this paper is to study and to test the numerical methods for stochastic differential equations with solutions on a given smooth manifold. Second-order cylindrical surfaces such as elliptic, hyperbolic, and parabolic cylinders are chosen as manifolds in three-dimensional space provided that the phase space is two-dimensional space. The classes of stochastic differential equations are formed for the considered manifolds and linear equations with multiplicative noise that are the particular case of these classes are concerned. The numerical methods accuracy as the mean distance between solutions and the given smooth manifold is estimated. The comparative analysis of the results obtained by using the different numerical methods is given.

KW - First integral

KW - Invariant

KW - Numerical method

KW - Random process

KW - Stochastic differential equation

UR - http://www.scopus.com/inward/record.url?scp=85040520758&partnerID=8YFLogxK

U2 - 10.1109/SIBIRCON.2017.8109832

DO - 10.1109/SIBIRCON.2017.8109832

M3 - Conference contribution

AN - SCOPUS:85040520758

SP - 34

EP - 37

BT - Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017

Y2 - 18 September 2017 through 22 September 2017

ER -

ID: 9133658