Frequency estimation of a sinusoidal signal with time-varying amplitude*

Standard

Frequency estimation of a sinusoidal signal with time-varying amplitude^*. / Vedyakov, Alexey A.; Vediakova, Anastasiia O.; Bobtsov, Alexey A.; Pyrkin, Anton A.; Aranovskiy, Stanislav V.

In: IFAC-PapersOnLine, Vol. 50, No. 1, 07.2017, p. 12880-12885.

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

Author

Vedyakov, Alexey A. ; Vediakova, Anastasiia O. ; Bobtsov, Alexey A. ; Pyrkin, Anton A. ; Aranovskiy, Stanislav V. / Frequency estimation of a sinusoidal signal with time-varying amplitude^*. In: IFAC-PapersOnLine. 2017 ; Vol. 50, No. 1. pp. 12880-12885.

BibTeX

@article{bf6bdb74b6b54d27b549e99967d2c2c2,

title = "Frequency estimation of a sinusoidal signal with time-varying amplitude*",

abstract = "This paper is devoted to frequency estimation of a sinusoidal signal with a time-varying amplitude. The amplitude can take zero values, but should be known and bounded. The first order linear regression model is obtained. The estimation algorithm has been constructed basing on standard gradient approach. It is shown that the frequency estimation error converges to zero exponentially fast. The described algorithm does not require measuring or calculating derivatives of the input signal. The efficiency of the proposed approach is demonstrated through a set of numerical simulations.",

keywords = "continuous time estimation, frequency estimation, gray box model, time-domain identification",

author = "Vedyakov, {Alexey A.} and Vediakova, {Anastasiia O.} and Bobtsov, {Alexey A.} and Pyrkin, {Anton A.} and Aranovskiy, {Stanislav V.}",

note = "Publisher Copyright: {\textcopyright} 2017 Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; 20th World Congress of the International-Federation-of-Automatic-Control (IFAC) ; Conference date: 09-07-2017 Through 14-07-2017",

year = "2017",

month = jul,

doi = "10.1016/j.ifacol.2017.08.1940",

language = "English",

volume = "50",

pages = "12880--12885",

journal = "IFAC-PapersOnLine",

issn = "2405-8963",

publisher = "Elsevier",

number = "1",

}

RIS

TY - JOUR

T1 - Frequency estimation of a sinusoidal signal with time-varying amplitude*

AU - Vedyakov, Alexey A.

AU - Vediakova, Anastasiia O.

AU - Bobtsov, Alexey A.

AU - Pyrkin, Anton A.

AU - Aranovskiy, Stanislav V.

PY - 2017/7

Y1 - 2017/7

N2 - This paper is devoted to frequency estimation of a sinusoidal signal with a time-varying amplitude. The amplitude can take zero values, but should be known and bounded. The first order linear regression model is obtained. The estimation algorithm has been constructed basing on standard gradient approach. It is shown that the frequency estimation error converges to zero exponentially fast. The described algorithm does not require measuring or calculating derivatives of the input signal. The efficiency of the proposed approach is demonstrated through a set of numerical simulations.

AB - This paper is devoted to frequency estimation of a sinusoidal signal with a time-varying amplitude. The amplitude can take zero values, but should be known and bounded. The first order linear regression model is obtained. The estimation algorithm has been constructed basing on standard gradient approach. It is shown that the frequency estimation error converges to zero exponentially fast. The described algorithm does not require measuring or calculating derivatives of the input signal. The efficiency of the proposed approach is demonstrated through a set of numerical simulations.

KW - continuous time estimation

KW - frequency estimation

KW - gray box model

KW - time-domain identification

UR - http://www.scopus.com/inward/record.url?scp=85040688259&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2017.08.1940

DO - 10.1016/j.ifacol.2017.08.1940

M3 - Article

AN - SCOPUS:85040688259

VL - 50

SP - 12880

EP - 12885

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 1

T2 - 20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

Y2 - 9 July 2017 through 14 July 2017

ER -

ID: 76548071