Journal of Siberian Federal University. Mathematics & Physics / On Non-parametric Models of Multidimensional Non-inertial Processes with Dependent input Variables

Full text (.pdf)
Issue
Journal of Siberian Federal University. Mathematics & Physics. 2017 10 (4)
Authors
Medvedev, Alexander V.; Chzhan, Ekaterina A.
Contact information
Medvedev, Alexander V.: Siberian State Aerospace University, Krasnoyarsky Rabochy, 31, Krasnoyarsk, 660014 Russia; ; Chzhan, Ekaterina A.: Institute of Information and Space Technology, Siberian Federal University, Svobodny, 79, Krasnoyarsk, 660041 Russia;
Keywords
non-parametric modeling; non-inertial processes with delay; indicator function; H-process
Abstract

The problem of identification of multidimensional non-inertial systems with delay is considered. Components 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 methods 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

Pages
514–521
Paper at repository of SibFU
https://elib.sfu-kras.ru/handle/2311/35018