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Title: On the dual stabilization of the multidimensional regression object at a given level
Authors: Mukha, V. S.
Kako, N. F.
Keywords: публикации ученых;dynamic programming;Gaussian noise;regression object
Issue Date: 2022
Publisher: Белорусский государственный университет
Citation: Mukha, V. S. On the dual stabilization of the multidimensional regression object at a given level / Mukha V. S., Kako N. F. // Computer Data Analysis and Modeling: Stochastics and Data Sciences : Proceedings of the XIII International Conference, Minsk, September 6–10, 2022 / ed.: Yu. Kharin [et al.]. – Minsk : BSU, 2022. – P. 126–130.
Abstract: The statement of the problem of the dual control of the regression object with multidimensional-matrix input and output variables and dynamic programming functional equations for its solution are given. The problem of the dual stabilization of the regression object at the given level is considered. In order to solve the problem, the regression function of the object is supposed to be affine in input variables, and the inner noise is supposed to be Gaussian. The optimal control action at the last control step is obtained and is proposed to be used at the arbitrary control step. The obtained control algorithm was programmed for numerical calculations and tested for a number of objects.
Appears in Collections:Публикации в изданиях Республики Беларусь

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