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A. A. Novosyolov

PARAMETRIZATION OF MODELS OF CONTROLLED SYSTEMS The paper describes application of orthogonal series method for construction of controlled systems models under

non-parametric uncertainty. A key element of the method is draw of orthogonal expansion length based on observa-tions, in other words, defining parametric structure of the model. The method is demonstrated for estimation of distribu-tion density and regression function. Directions for generalizing onto multi-dimensional case are also presented.

Keywords: distribution density, regression function, orthogonal series, non-parametric estimate.

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I. A. Pestunov, V. B. Berikov, Yu. N. Sinyavskiy

ALGORITHM FOR MULTISPECTRAL IMAGE SEGMENTATION BASED

ON ENSEMBLE OF NONPARAMETRIC CLUSTERING ALGORITHMS

The method for constructing an ensemble of nonparametric clustering algorithms is proposed. Its theoretical sub-stantiation is resulted. Results of the model data and real images confirm the efficiency of the proposed method.

Keywords: multispectral image segmentation, nonparametric clustering algorithms, ensemble approach.

. ., . ., . ., 2010

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