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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/53732
Title: Orthogonal Polynomials and Fourier Series for Functions of Vector Variable: Multidimensional-Matrix Approach
Authors: Mukha, V. S.
Keywords: публикации ученых;fourier series;multivariate polynomial regression;multidimensional-matrix;orthogonal polynomials
Issue Date: 2023
Publisher: Ms. M. B. Mondal, Ph.D.
Citation: Mukha, V. S. Orthogonal Polynomials and Fourier Series for Functions of Vector Variable: Multidimensional-Matrix Approach / V. S. Mukha // Asian Journal of Probability and Statistics. – 2023. – Vol. 25, issue 3. – P. 84–98.
Abstract: In the article, the theory of the Fourier series on the orthogonal multidimensional-matrix polynomials is developed. The known results from the theory of the orthogonal polynomials of the vector variable and the Fourier series are given and the new results are presented. In particular, the known results of the Fourier series are extended to the case of the multidimensional-matrix functions, what allows us to solve more general approximation problems. The general case of the approximation of the multidimensional-matrix function of the vector argument by the Fourier series on the orthogonal multidimensional-matrix polynomials is realized programmatically as the program function and its efficiency is confirmed. The analytical expressions for the coefficients of the second degree orthogonal polynomials and Fourier series for the potential studies are obtained.
URI: https://libeldoc.bsuir.by/handle/123456789/53732
DOI: https://doi.org/10.9734/ajpas/2023/v25i3565
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