Applicational possibilities of nonparametric estimation of distribution density for control engineering

• Autorzy: Kulczycki P.
• Języki publikacji: EN

Abstrakty

EN

Together with the dynamic development of modern computer systems, the possibilities of applying refined methods of nonparametric estimation to control engineering tasks have grown just as fast. This broad and complex theme is presented in this paper for the case of estimation of density of a random variable distribution. Nonparametric methods allow here the useful characterization of probability distributions without arbitrary assumptions regarding their membership to a fixed class. Following an illustratory description of the fundamental procedures used to this end, results will be generalized and synthetically presented of research on the application of kernel estimators, dominant here, in problems of Bayes parameter estimation with asymmetrical polynomial loss function, as well as for fault detection in dynamical systems as objects of automatic control, in the scope of detection, diagnosis and prognosis of malfunctions. To this aim the basics of data analysis and exploration tasks – recognition of outliers, clustering and classification – solved using uniform mathematical apparatus based on the kernel estimators methodology were also investigated.

Słowa kluczowe

EN

control engineering; nonparametric estimation; density of probability distribution; kernel estimators

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2008
• Tom: Vol. 56, nr 4
• Strony: 347--359
• Opis fizyczny: Bibliogr. 58 poz., rys.

Twórcy

autor

Kulczycki P.

• Department of Automatic Control, Cracow University of Technology, 24 Warszawska St., 31-155 Cracow, Poland Systems Research Institute, Polish Academy of Sciences, 6 Newelska St., 01-447 Warsaw, Poland

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