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Journal of Automation and Information Sciences

Erscheint 12 Ausgaben pro Jahr

ISSN Druckformat: 1064-2315

ISSN Online: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

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Parameter Estimation Algorithm of the Linear Regression with Bounded Noise in Measurements of All Variables

Volumen 45, Ausgabe 4, 2013, pp. 1-15
DOI: 10.1615/JAutomatInfScien.v45.i4.10
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ABSTRAKT

Nonconvex set of values of parameters consistent with the current measurement of the input and output variables is represented as the union of a finite number of convex subsets. The solution of the estimation problem is reduced to choosing one of the subsets and solving the obtained system of convex inequalities. This problem is solved using the previously proposed ellipsoid method modification which works in case of a finite number of incompatible inequalities. Computational cost of the proposed algorithm is compared with that of similar estimation problem without noise. The properties of the algorithm are illustrated by numerical examples.

REFERENZIERT VON
  1. Gubarev V. F., Salnikov N. N., Melnychuk S. V., Identification of Regularized Models in the Linear Regression Class, Cybernetics and Systems Analysis, 57, 4, 2021. Crossref

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