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Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2017-17-5-952-955
NEW ALGORITHM OF VARIABLE PARAMETERS IDENTIFICATION FOR LINEAR REGRESSION MODEL
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Article in Russian
For citation: Le Van Tuan, Bobtsov A.A., Pyrkin A.A. New algorithm of variable parameters identification for linear regression model. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2017, vol. 17, no. 5, pp. 952–955 (in Russian). doi: 10.17586/2226-1494-2017-17-5-952-955
Abstract
For citation: Le Van Tuan, Bobtsov A.A., Pyrkin A.A. New algorithm of variable parameters identification for linear regression model. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2017, vol. 17, no. 5, pp. 952–955 (in Russian). doi: 10.17586/2226-1494-2017-17-5-952-955
Abstract
This brief paper discusses identification problem of unknown time-varying parameters for a linear regression model. A new algorithm is proposed that guarantees–in case of a set of assumptions existence–an estimate of unknown parameters and their dynamical model with an asymptoticallyzero error. We analyze in details the case with two unknown parameters that enables to understand the main idea of the proposed approach. The efficiency of the algorithm considered in the paper is illustrated by computer modeling.
Keywords: parameters identification, linear regression model, DREM
Acknowledgements. This work is supported by the Russian Science Foundation, project No.16-11-00049.
References
Acknowledgements. This work is supported by the Russian Science Foundation, project No.16-11-00049.
References
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