Standard

The multi-harmonic signal frequencies estimation in finite time. / Vediakova, A. O.; Vedyakov, A. A.; Pyrkin, A. A.; Bobtsov, A. A.; Gromov, V. S.

в: Journal of Physics: Conference Series, Том 1864, № 1, 012116, 20.05.2021.

Результаты исследований: Научные публикации в периодических изданияхстатья в журнале по материалам конференцииРецензирование

Harvard

Vediakova, AO, Vedyakov, AA, Pyrkin, AA, Bobtsov, AA & Gromov, VS 2021, 'The multi-harmonic signal frequencies estimation in finite time', Journal of Physics: Conference Series, Том. 1864, № 1, 012116. https://doi.org/10.1088/1742-6596/1864/1/012116

APA

Vediakova, A. O., Vedyakov, A. A., Pyrkin, A. A., Bobtsov, A. A., & Gromov, V. S. (2021). The multi-harmonic signal frequencies estimation in finite time. Journal of Physics: Conference Series, 1864(1), [012116]. https://doi.org/10.1088/1742-6596/1864/1/012116

Vancouver

Vediakova AO, Vedyakov AA, Pyrkin AA, Bobtsov AA, Gromov VS. The multi-harmonic signal frequencies estimation in finite time. Journal of Physics: Conference Series. 2021 Май 20;1864(1). 012116. https://doi.org/10.1088/1742-6596/1864/1/012116

Author

Vediakova, A. O. ; Vedyakov, A. A. ; Pyrkin, A. A. ; Bobtsov, A. A. ; Gromov, V. S. / The multi-harmonic signal frequencies estimation in finite time. в: Journal of Physics: Conference Series. 2021 ; Том 1864, № 1.

BibTeX

@article{8b258e544b4f476fb3cbd5374181df3e,
title = "The multi-harmonic signal frequencies estimation in finite time",
abstract = "The paper presents a method to estimate the frequencies of a multi-harmonic signal in finite time. We use parameterization based on applying delay operators to a measurable signal. The result is a linear regression model with an unknown vector which depends on the signal parameters. We use Dynamic Regressor Extension and Mixing method to replace the n-th order regression model with scalar regressions. After that, we estimate the parameters separately using the standard gradient descent method. In the last step, we find algebraically the finite-time parameter estimates. The set of numerical simulations demonstrates the efficiency of the proposed approach.",
author = "Vediakova, {A. O.} and Vedyakov, {A. A.} and Pyrkin, {A. A.} and Bobtsov, {A. A.} and Gromov, {V. S.}",
note = "Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd.; 13th Multiconference on Control Problems, MCCP 2020 ; Conference date: 06-10-2020 Through 08-10-2020",
year = "2021",
month = may,
day = "20",
doi = "10.1088/1742-6596/1864/1/012116",
language = "English",
volume = "1864",
journal = "Journal of Physics: Conference Series",
issn = "1742-6588",
publisher = "IOP Publishing Ltd.",
number = "1",
url = "http://www.elektropribor.spb.ru/nauchnaya-deyatelnost/xiii-mkpu/index3.php",

}

RIS

TY - JOUR

T1 - The multi-harmonic signal frequencies estimation in finite time

AU - Vediakova, A. O.

AU - Vedyakov, A. A.

AU - Pyrkin, A. A.

AU - Bobtsov, A. A.

AU - Gromov, V. S.

N1 - Conference code: 13

PY - 2021/5/20

Y1 - 2021/5/20

N2 - The paper presents a method to estimate the frequencies of a multi-harmonic signal in finite time. We use parameterization based on applying delay operators to a measurable signal. The result is a linear regression model with an unknown vector which depends on the signal parameters. We use Dynamic Regressor Extension and Mixing method to replace the n-th order regression model with scalar regressions. After that, we estimate the parameters separately using the standard gradient descent method. In the last step, we find algebraically the finite-time parameter estimates. The set of numerical simulations demonstrates the efficiency of the proposed approach.

AB - The paper presents a method to estimate the frequencies of a multi-harmonic signal in finite time. We use parameterization based on applying delay operators to a measurable signal. The result is a linear regression model with an unknown vector which depends on the signal parameters. We use Dynamic Regressor Extension and Mixing method to replace the n-th order regression model with scalar regressions. After that, we estimate the parameters separately using the standard gradient descent method. In the last step, we find algebraically the finite-time parameter estimates. The set of numerical simulations demonstrates the efficiency of the proposed approach.

UR - http://www.scopus.com/inward/record.url?scp=85107441660&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1864/1/012116

DO - 10.1088/1742-6596/1864/1/012116

M3 - Conference article

AN - SCOPUS:85107441660

VL - 1864

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012116

T2 - 13th Multiconference on Control Problems, MCCP 2020

Y2 - 6 October 2020 through 8 October 2020

ER -

ID: 88150644