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Scattered data points best interpolation as a problem of the best recovery in the sense of Sard
Author(s) -
Natasha Danailova
Publication year - 2009
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil0902028d
Subject(s) - mathematics , interpolation (computer graphics) , bivariate analysis , kernel (algebra) , combinatorics , function (biology) , derivative (finance) , product (mathematics) , discrete mathematics , algorithm , mathematical analysis , geometry , statistics , computer science , economics , biology , animation , computer graphics (images) , evolutionary biology , financial economics
The problem of the best recovery in the sense of Sard of a linear functional Lf on the basis of information T (f) = fLjf; j = 1; 2; : : : ; Ng is studied. It is shown that in the class of bivariate functions with restricted (n; m) -derivative, known on the (n; m)-grid lines, the problem of the best recovery of a linear functional leads to the best approximation of L(KnKm) in the space S = spanfLj(Kn Km); j = 1; 2; : : : ; Ng, where Kn(x; t) = K(x; t) Lxn(K(:; t); x) is the dierence between the truncated power kernel K(x; t) = (x t)n 1 + =(n 1)! and its Lagrange interpolation formula. In particular, the best recovery of a bivariate function is considered, if scattered data points and blending grid are given. An algorithm is designed and realized using the software product MATLAB.

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