On non-parametric models of multidimensional non-inertial processes with dependent input variables

Тип публикации: статья из журнала

Год издания: 2017

Идентификатор DOI: 10.17516/1997-1397-2017-10-4-514-521

Ключевые слова: H-process, Indicator function, Non-inertial processes with delay, Non-parametric modeling

Аннотация: The problem of identification of multidimensional non-inertial systems with delay is considered. Com- ponents of the input vector are stochastically related, and this relationship is unknown a priori. Such processes have “tubular” structure in the space of the input and output variables. In this situation meth- ods of identification theory of non-inertial systems are not applicable. In general, it is not known a priori whether the process has “tubular” structure or not. To clear up this question the problem of estimation of the volume of a subdomain where “tubular” process takes place is considered. The initial data for this problem follows from the measurement of input-output variables. An algorithm for estimating the volume of the “tubular” subdomain in relation to the volume of the investigated process is suggested. The volume of the investigated process is always known from a priori information or production schedules. Numerical experiments are carried out with the use of the method of statistical modeling. They show high effectiveness of the proposed algorithm. © Siberian Federal University. All rights reserved.

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Издание

Журнал: Journal of Siberian Federal University - Mathematics and Physics

Выпуск журнала: Vol. 10, Is. 4

Номера страниц: 514-521

ISSN журнала: 19971397

Издатель: Siberian Federal University

Авторы

  • Medvedev A.V. (Siberian State Aerospace University, Krasnoyarsky Rabochy, 31, Krasnoyarsk, Russian Federation)
  • Chzhan E.A. (Institute of Information and Space Technology, Siberian Federal University, Svobodny, 79, Krasnoyarsk, Russian Federation)

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