Nonlinear parametric identification based on the criterion of minimum probability of estimation error |
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Authors: | S. V. Sokolov P. A. Kucherenko |
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Affiliation: | (1) Rostov Technical University of Communications, pl. Narodnii Opolchenie 2, 344038 Rostov-on-Don, Russia |
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Abstract: | The importance of studies of alternative (as compared to traditional) methods of nonlinear stochastic parametric identification is demonstrated. Synthesis of a procedure of identification of the parameter, “discrete observer,” with the use of the criterion, “minimum probability of estimation error,” is proposed for the first time. A model example that demonstrates the efficiency of the proposed approach is considered. |
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Keywords: | digital signal processing nonlinear parametric identification stochastic discrete object optimal discrete Kalman filter |
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