Applications of classical approximation theory to periodic basis function networks and computational harmonic analysis

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Abstract

In this paper, we describe a novel approach to classical approximation theory of periodic univariate and multivariate functions by trigonometric polynomials. While classical wisdom holds that such approximation is too sensitive to the lack of smoothness of the target functions at isolated points, our constructions show how to overcome this problem. We describe applications to approximation by periodic basis function networks, and indicate further research in the direction of Jacobi expansion and approximation on the Euclidean sphere. While the paper is mainly intended to be a survey of our recent research in these directions, several results are proved for the first time here.

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Mhaskar, H. N., Nevai, P., & Shvarts, E. (2013). Applications of classical approximation theory to periodic basis function networks and computational harmonic analysis. Bulletin of Mathematical Sciences, 3(3), 485–549. https://doi.org/10.1007/s13373-013-0043-1

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