Standard

Estimation of unknown function point of minima observed in the presence of dependent noises. / Granichin, O. N.

In: Problemy Peredachi Informatsii, Vol. 28, No. 2, 01.04.1992, p. 16-20.

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

Harvard

Granichin, ON 1992, 'Estimation of unknown function point of minima observed in the presence of dependent noises', Problemy Peredachi Informatsii, vol. 28, no. 2, pp. 16-20.

APA

Granichin, O. N. (1992). Estimation of unknown function point of minima observed in the presence of dependent noises. Problemy Peredachi Informatsii, 28(2), 16-20.

Vancouver

Granichin ON. Estimation of unknown function point of minima observed in the presence of dependent noises. Problemy Peredachi Informatsii. 1992 Apr 1;28(2):16-20.

Author

Granichin, O. N. / Estimation of unknown function point of minima observed in the presence of dependent noises. In: Problemy Peredachi Informatsii. 1992 ; Vol. 28, No. 2. pp. 16-20.

BibTeX

@article{b2c0bf76ad714a4cb1a1008eb59d5f54,
title = "Estimation of unknown function point of minima observed in the presence of dependent noises",
abstract = "The stochastic approximation type algorithm with input disturbance is proposed. The algorithm enables to form consistent estimates of unknown function point of minima which depend on random parameter in the presence of correlated noises. The algorithm convergence is proved under assumption that disturbance and noises are independent. The algorithm is illustrated for the example of identification of mean values of parameters of non-stationary moving average process.",
author = "Granichin, {O. N.}",
year = "1992",
month = apr,
day = "1",
language = "English",
volume = "28",
pages = "16--20",
journal = "ПРОБЛЕМЫ ПЕРЕДАЧИ ИНФОРМАЦИИ",
issn = "0555-2923",
publisher = "Издательство {"}Наука{"}",
number = "2",

}

RIS

TY - JOUR

T1 - Estimation of unknown function point of minima observed in the presence of dependent noises

AU - Granichin, O. N.

PY - 1992/4/1

Y1 - 1992/4/1

N2 - The stochastic approximation type algorithm with input disturbance is proposed. The algorithm enables to form consistent estimates of unknown function point of minima which depend on random parameter in the presence of correlated noises. The algorithm convergence is proved under assumption that disturbance and noises are independent. The algorithm is illustrated for the example of identification of mean values of parameters of non-stationary moving average process.

AB - The stochastic approximation type algorithm with input disturbance is proposed. The algorithm enables to form consistent estimates of unknown function point of minima which depend on random parameter in the presence of correlated noises. The algorithm convergence is proved under assumption that disturbance and noises are independent. The algorithm is illustrated for the example of identification of mean values of parameters of non-stationary moving average process.

UR - http://www.scopus.com/inward/record.url?scp=0026846604&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0026846604

VL - 28

SP - 16

EP - 20

JO - ПРОБЛЕМЫ ПЕРЕДАЧИ ИНФОРМАЦИИ

JF - ПРОБЛЕМЫ ПЕРЕДАЧИ ИНФОРМАЦИИ

SN - 0555-2923

IS - 2

ER -

ID: 32481362