Orthoregressional-algebraic parameter identification method for linear differential equations
Sibirskij žurnal čistoj i prikladnoj matematiki, Tome 18 (2018) no. 1, pp. 73-90 Cet article a éte moissonné depuis la source Math-Net.Ru

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A combined orthoregressional-algebraic approach to the parameter identification of linear differential equations from solution measurements with additive noise is proposed. It is based on the algebraic Fliess–Sira-Ramirez method in conjunction with the orthogonal regression (TLS) method in the space of measurements transformed by the integral operators of convolution type. The consistency of the orthoregressional-algebraic method is established and a numerical comparison with the asymptotically optimal variational identification method is performed.
Keywords: linear differential equations, parameter identification, algebraic method, variational identification method, total least squares, orthoregressional-algebraic method, consistency.
Mots-clés : orthogonal regression
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A. A. Lomov. Orthoregressional-algebraic parameter identification method for linear differential equations. Sibirskij žurnal čistoj i prikladnoj matematiki, Tome 18 (2018) no. 1, pp. 73-90. http://geodesic.mathdoc.fr/item/VNGU_2018_18_1_a6/

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