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Journal of Automation and Information Sciences
SJR: 0.238 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimer: 1064-2315
ISSN En ligne: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v40.i5.40
pages 52-60

Nonlinear Parametric Identification Based on the Generalized Probabilistic Criteria

Sergey V. Sokolov
Rostov State University of Railway Transport (Russia)
Pavel A. Kucherenko
Rostov State University of Railway Communication, Rostov-on-Don, Russia

RÉSUMÉ

The urgency of investigating the alternative (with respect to the traditional) methods of stochastic nonlinear parametric identification is shown. The solution of the problem on the parametric identification based on the generalized probabilistic criteria is proposed. The identification algorithm based on the minimum criterion of the estimation error probability is synthesized. The results of the experimental modeling which demonstrate an efficiency of the proposed method are presented.


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