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Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization. / Vakhitov, A. T.; Granichin, O. N.; Gurevich, L. S.

In: Automation and Remote Control, Vol. 70, No. 11, 11.2009, p. 1827-1835.

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

Harvard

Vakhitov, AT, Granichin, ON & Gurevich, LS 2009, 'Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization', Automation and Remote Control, vol. 70, no. 11, pp. 1827-1835. https://doi.org/10.1134/S000511790911006X, https://doi.org/10.1134/S000511790911006X

APA

Vakhitov, A. T., Granichin, O. N., & Gurevich, L. S. (2009). Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization. Automation and Remote Control, 70(11), 1827-1835. https://doi.org/10.1134/S000511790911006X, https://doi.org/10.1134/S000511790911006X

Vancouver

Vakhitov AT, Granichin ON, Gurevich LS. Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization. Automation and Remote Control. 2009 Nov;70(11):1827-1835. https://doi.org/10.1134/S000511790911006X, https://doi.org/10.1134/S000511790911006X

Author

Vakhitov, A. T. ; Granichin, O. N. ; Gurevich, L. S. / Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization. In: Automation and Remote Control. 2009 ; Vol. 70, No. 11. pp. 1827-1835.

BibTeX

@article{8dfd5027233440f8aa2bbd1959162202,
title = "Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization",
abstract = "Consideration was given to the randomized stochastic approximation algorithm with simultaneous trial input perturbation and two measurements used to optimize the unconstrained nonstationary functional. The upper boundary of the mean-square residual was established under conditions of single differentiability of the functional and almost arbitrary noise. Efficiency of the algorithm was illustrated by an example of stabilization of the resulting estimates for the multidimensional case under dependent observation noise.",
author = "Vakhitov, {A. T.} and Granichin, {O. N.} and Gurevich, {L. S.}",
year = "2009",
month = nov,
doi = "10.1134/S000511790911006X",
language = "Английский",
volume = "70",
pages = "1827--1835",
journal = "Automation and Remote Control",
issn = "0005-1179",
publisher = "МАИК {"}Наука/Интерпериодика{"}",
number = "11",

}

RIS

TY - JOUR

T1 - Algorithm for stochastic approximation with trial input perturbation in the nonstationary problem of optimization

AU - Vakhitov, A. T.

AU - Granichin, O. N.

AU - Gurevich, L. S.

PY - 2009/11

Y1 - 2009/11

N2 - Consideration was given to the randomized stochastic approximation algorithm with simultaneous trial input perturbation and two measurements used to optimize the unconstrained nonstationary functional. The upper boundary of the mean-square residual was established under conditions of single differentiability of the functional and almost arbitrary noise. Efficiency of the algorithm was illustrated by an example of stabilization of the resulting estimates for the multidimensional case under dependent observation noise.

AB - Consideration was given to the randomized stochastic approximation algorithm with simultaneous trial input perturbation and two measurements used to optimize the unconstrained nonstationary functional. The upper boundary of the mean-square residual was established under conditions of single differentiability of the functional and almost arbitrary noise. Efficiency of the algorithm was illustrated by an example of stabilization of the resulting estimates for the multidimensional case under dependent observation noise.

U2 - 10.1134/S000511790911006X

DO - 10.1134/S000511790911006X

M3 - статья

VL - 70

SP - 1827

EP - 1835

JO - Automation and Remote Control

JF - Automation and Remote Control

SN - 0005-1179

IS - 11

ER -

ID: 5014786