Operator-orthoregressive methods for identifying coefficients of linear difference equations

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Operator-orthoregressive methods for identifying coefficients of linear difference equations. / Lomov, A. A.

в: Siberian Electronic Mathematical Reports, Том 18, № 2, 11, 2021, стр. 792-804.

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

BibTeX

@article{c072599c9ac740c8a0ceedc61dd8c3f9,

title = "Operator-orthoregressive methods for identifying coefficients of linear difference equations",

abstract = "We propose a new family of operator-orthoregressive methods for identifying the coefficients of linear difference equations from measurements of noisy solution at short time intervals. This family includes special cases of orthogonal regression (TLS) and variational identification (STLS) methods. The conditions of identifiability, as well as quantitative indicators of local identifiability, based on the numerical characteristics of the ellipsoids of deviations of the identified coefficients at small disturbances in measurements, are obtained. Computational algorithms are mentioned.",

keywords = "algebraic Fliess method, linear difference equations, operator-orthoregressive method, orthogonal regression method, parameter identification, Prony problem, quantitative local identifiability indicators, variational identification method",

author = "Lomov, {A. A.}",

note = "Funding Information: This work was supported by the Russian Foundation for Basic Research (project No. 19-01-00754). Funding Information: Lomov, A.A., Operator-orthoregressive methods for identifying coefficients of linear difference equations. {\textcopyright} 2021 Lomov A.A. The work is supported by RFFI (grant 19-01-00754). Received December, 28, 2020, published July, 14, 2021. Publisher Copyright: {\textcopyright} 2021 Lomov A.A. All Rights Reserved.",

year = "2021",

doi = "10.33048/semi.2021.18.058",

language = "English",

volume = "18",

pages = "792--804",

journal = "Сибирские электронные математические известия",

issn = "1813-3304",

publisher = "Sobolev Institute of Mathematics",

number = "2",

}

RIS

TY - JOUR

T1 - Operator-orthoregressive methods for identifying coefficients of linear difference equations

AU - Lomov, A. A.

N1 - Funding Information: This work was supported by the Russian Foundation for Basic Research (project No. 19-01-00754). Funding Information: Lomov, A.A., Operator-orthoregressive methods for identifying coefficients of linear difference equations. © 2021 Lomov A.A. The work is supported by RFFI (grant 19-01-00754). Received December, 28, 2020, published July, 14, 2021. Publisher Copyright: © 2021 Lomov A.A. All Rights Reserved.

PY - 2021

Y1 - 2021

N2 - We propose a new family of operator-orthoregressive methods for identifying the coefficients of linear difference equations from measurements of noisy solution at short time intervals. This family includes special cases of orthogonal regression (TLS) and variational identification (STLS) methods. The conditions of identifiability, as well as quantitative indicators of local identifiability, based on the numerical characteristics of the ellipsoids of deviations of the identified coefficients at small disturbances in measurements, are obtained. Computational algorithms are mentioned.

AB - We propose a new family of operator-orthoregressive methods for identifying the coefficients of linear difference equations from measurements of noisy solution at short time intervals. This family includes special cases of orthogonal regression (TLS) and variational identification (STLS) methods. The conditions of identifiability, as well as quantitative indicators of local identifiability, based on the numerical characteristics of the ellipsoids of deviations of the identified coefficients at small disturbances in measurements, are obtained. Computational algorithms are mentioned.

KW - algebraic Fliess method

KW - linear difference equations

KW - operator-orthoregressive method

KW - orthogonal regression method

KW - parameter identification

KW - Prony problem

KW - quantitative local identifiability indicators

KW - variational identification method

UR - http://www.scopus.com/inward/record.url?scp=85110602461&partnerID=8YFLogxK

UR - https://www.elibrary.ru/item.asp?id=46898602

U2 - 10.33048/semi.2021.18.058

DO - 10.33048/semi.2021.18.058

M3 - Article

AN - SCOPUS:85110602461

VL - 18

SP - 792

EP - 804

JO - Сибирские электронные математические известия

JF - Сибирские электронные математические известия

SN - 1813-3304

IS - 2

M1 - 11

ER -

ID: 34152426