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JOURNALS // Sibirskie Èlektronnye Matematicheskie Izvestiya [Siberian Electronic Mathematical Reports] // Archive

Sib. Èlektron. Mat. Izv., 2021 Volume 18, Issue 2, Pages 792–804 (Mi semr1400)

Computational mathematics

Operator-orthoregressive methods for identifying coefficients of linear difference equations

A. A. Lomovab

a Sobolev Institute of Mathematics, 4, Koptyuga ave., Novosibirsk, 630090, Russia
b Novosibirsk State University, 1, Pirogova str., Novosibirsk, 630090, Russia

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

UDC: 519.6

MSC: 65F15, 41A30

Received December 28, 2020, published July 14, 2021

Language: English

DOI: 10.33048/semi.2021.18.058



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