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Identification of Piecewise Linear Parameters of Regression Models of Non-Stationary Deterministic Systems

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Abstract

We consider the problem of identifying unknown nonstationary piecewise linear parameters for a linear regression model. A new algorithm is proposed that allows, in the case of a number of assumptions on the elements of the regressor, to provide an estimate of unknown non-stationary parameters. We analyze in detail the case with two unknown parameters, which makes it possible to understand the main idea of the proposed approach. We also consider a generalization to the case of an arbitrary number of parameters. We give an example of computer simulation that illustrates the efficiency of the proposed approach.

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Correspondence to Jian Wang.

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Original Russian Text © Jian Wang, Tuan Le Van, A.A. Pyrkin, S.A. Kolyubin, A.A. Bobtsov, 2018, published in Avtomatika i Telemekhanika, 2018, No. 12, pp. 71–82.

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Wang, J., Le Vang, T., Pyrkin, A.A. et al. Identification of Piecewise Linear Parameters of Regression Models of Non-Stationary Deterministic Systems. Autom Remote Control 79, 2159–2168 (2018). https://doi.org/10.1134/S0005117918120068

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  • DOI: https://doi.org/10.1134/S0005117918120068

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