Standard

Optimal Convergence Rate of the Randomized Algorithms of Stochastic Approximation in Arbitrary Noise. / Granichin, O. N.

In: Automation and Remote Control, Vol. 64, No. 2, 01.01.2003, p. 252-262.

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

Harvard

Granichin, ON 2003, 'Optimal Convergence Rate of the Randomized Algorithms of Stochastic Approximation in Arbitrary Noise', Automation and Remote Control, vol. 64, no. 2, pp. 252-262. https://doi.org/10.1023/A:1022263014535

APA

Granichin, O. N. (2003). Optimal Convergence Rate of the Randomized Algorithms of Stochastic Approximation in Arbitrary Noise. Automation and Remote Control, 64(2), 252-262. https://doi.org/10.1023/A:1022263014535

Vancouver

Granichin ON. Optimal Convergence Rate of the Randomized Algorithms of Stochastic Approximation in Arbitrary Noise. Automation and Remote Control. 2003 Jan 1;64(2):252-262. https://doi.org/10.1023/A:1022263014535

Author

Granichin, O. N. / Optimal Convergence Rate of the Randomized Algorithms of Stochastic Approximation in Arbitrary Noise. In: Automation and Remote Control. 2003 ; Vol. 64, No. 2. pp. 252-262.

BibTeX

@article{a94ad4c48d8b47b29613a0ca8abf61e0,
title = "Optimal Convergence Rate of the Randomized Algorithms of Stochastic Approximation in Arbitrary Noise",
abstract = "Multidimensional stochastic optimization plays an important role in analysis and control of many technical systems. To solve the challenging multidimensional problems of optimization, it was suggested to use the randomized algorithms of stochastic approximation with perturbed input which are not just simple, but also provide consistent estimates of the unknown parameters for observations in {"}almost arbitrary{"} noise. Optimal methods of choosing the parameters of algorithms were motivated.",
keywords = "PERTURBATION GRADIENT APPROXIMATION",
author = "Granichin, {O. N.}",
year = "2003",
month = jan,
day = "1",
doi = "10.1023/A:1022263014535",
language = "English",
volume = "64",
pages = "252--262",
journal = "Automation and Remote Control",
issn = "0005-1179",
publisher = "МАИК {"}Наука/Интерпериодика{"}",
number = "2",

}

RIS

TY - JOUR

T1 - Optimal Convergence Rate of the Randomized Algorithms of Stochastic Approximation in Arbitrary Noise

AU - Granichin, O. N.

PY - 2003/1/1

Y1 - 2003/1/1

N2 - Multidimensional stochastic optimization plays an important role in analysis and control of many technical systems. To solve the challenging multidimensional problems of optimization, it was suggested to use the randomized algorithms of stochastic approximation with perturbed input which are not just simple, but also provide consistent estimates of the unknown parameters for observations in "almost arbitrary" noise. Optimal methods of choosing the parameters of algorithms were motivated.

AB - Multidimensional stochastic optimization plays an important role in analysis and control of many technical systems. To solve the challenging multidimensional problems of optimization, it was suggested to use the randomized algorithms of stochastic approximation with perturbed input which are not just simple, but also provide consistent estimates of the unknown parameters for observations in "almost arbitrary" noise. Optimal methods of choosing the parameters of algorithms were motivated.

KW - PERTURBATION GRADIENT APPROXIMATION

UR - http://www.scopus.com/inward/record.url?scp=84904243564&partnerID=8YFLogxK

U2 - 10.1023/A:1022263014535

DO - 10.1023/A:1022263014535

M3 - Article

AN - SCOPUS:84904243564

VL - 64

SP - 252

EP - 262

JO - Automation and Remote Control

JF - Automation and Remote Control

SN - 0005-1179

IS - 2

ER -

ID: 32480662