Standard

Finite Time Frequency Estimation for Multi-Sinusoidal Signals. / Vediakova, Anastasiia O.; Vedyakov, Alexey A.; Pyrkin, Anton A.; Bobtsov, Alexey A.; Gromov, Vladislav S.

в: European Journal of Control, Том 59, 01.05.2021, стр. 38-46.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Vediakova, AO, Vedyakov, AA, Pyrkin, AA, Bobtsov, AA & Gromov, VS 2021, 'Finite Time Frequency Estimation for Multi-Sinusoidal Signals', European Journal of Control, Том. 59, стр. 38-46. https://doi.org/10.1016/j.ejcon.2021.01.004

APA

Vediakova, A. O., Vedyakov, A. A., Pyrkin, A. A., Bobtsov, A. A., & Gromov, V. S. (2021). Finite Time Frequency Estimation for Multi-Sinusoidal Signals. European Journal of Control, 59, 38-46. https://doi.org/10.1016/j.ejcon.2021.01.004

Vancouver

Vediakova AO, Vedyakov AA, Pyrkin AA, Bobtsov AA, Gromov VS. Finite Time Frequency Estimation for Multi-Sinusoidal Signals. European Journal of Control. 2021 Май 1;59:38-46. https://doi.org/10.1016/j.ejcon.2021.01.004

Author

Vediakova, Anastasiia O. ; Vedyakov, Alexey A. ; Pyrkin, Anton A. ; Bobtsov, Alexey A. ; Gromov, Vladislav S. / Finite Time Frequency Estimation for Multi-Sinusoidal Signals. в: European Journal of Control. 2021 ; Том 59. стр. 38-46.

BibTeX

@article{fd17be52fca0423c8de8470101da8bf2,
title = "Finite Time Frequency Estimation for Multi-Sinusoidal Signals",
abstract = "The paper presents a method to estimate frequencies of a multi-sinusoidal signal in finite time. Expressing the signal via delayed measurements, we transform this nonlinear problem into a linear regression, where unknown parameters depend on signal frequencies. Dynamic Regressor Extension and Mixing method is used to replace nth order regression model with scalar regression. After, the parameters are estimated separately with the standard gradient descent method. On the last step, the finite time frequency estimate is found algebraically. In contrast to the standard gradient descent method, there is not a trade-off between estimation duration and sensitivity to measurement noise.",
keywords = "continuous-time estimation, finite time estimator, online frequency estimation, IDENTIFICATION, continuous-time estimation, finite time estimator, online frequency estimation",
author = "Vediakova, {Anastasiia O.} and Vedyakov, {Alexey A.} and Pyrkin, {Anton A.} and Bobtsov, {Alexey A.} and Gromov, {Vladislav S.}",
note = "Publisher Copyright: {\textcopyright} 2021 European Control Association Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = may,
day = "1",
doi = "10.1016/j.ejcon.2021.01.004",
language = "English",
volume = "59",
pages = "38--46",
journal = "European Journal of Control",
issn = "0947-3580",
publisher = "Lavoisier",

}

RIS

TY - JOUR

T1 - Finite Time Frequency Estimation for Multi-Sinusoidal Signals

AU - Vediakova, Anastasiia O.

AU - Vedyakov, Alexey A.

AU - Pyrkin, Anton A.

AU - Bobtsov, Alexey A.

AU - Gromov, Vladislav S.

N1 - Publisher Copyright: © 2021 European Control Association Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/5/1

Y1 - 2021/5/1

N2 - The paper presents a method to estimate frequencies of a multi-sinusoidal signal in finite time. Expressing the signal via delayed measurements, we transform this nonlinear problem into a linear regression, where unknown parameters depend on signal frequencies. Dynamic Regressor Extension and Mixing method is used to replace nth order regression model with scalar regression. After, the parameters are estimated separately with the standard gradient descent method. On the last step, the finite time frequency estimate is found algebraically. In contrast to the standard gradient descent method, there is not a trade-off between estimation duration and sensitivity to measurement noise.

AB - The paper presents a method to estimate frequencies of a multi-sinusoidal signal in finite time. Expressing the signal via delayed measurements, we transform this nonlinear problem into a linear regression, where unknown parameters depend on signal frequencies. Dynamic Regressor Extension and Mixing method is used to replace nth order regression model with scalar regression. After, the parameters are estimated separately with the standard gradient descent method. On the last step, the finite time frequency estimate is found algebraically. In contrast to the standard gradient descent method, there is not a trade-off between estimation duration and sensitivity to measurement noise.

KW - continuous-time estimation

KW - finite time estimator

KW - online frequency estimation

KW - IDENTIFICATION

KW - continuous-time estimation

KW - finite time estimator

KW - online frequency estimation

UR - http://www.scopus.com/inward/record.url?scp=85101853074&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/12b28329-386a-317a-a0ab-fc1723dec687/

U2 - 10.1016/j.ejcon.2021.01.004

DO - 10.1016/j.ejcon.2021.01.004

M3 - Article

AN - SCOPUS:85101853074

VL - 59

SP - 38

EP - 46

JO - European Journal of Control

JF - European Journal of Control

SN - 0947-3580

ER -

ID: 76547250