
doi: 10.1137/140993752
handle: 11449/162043
Summary: The present paper is a continuation of a recent article [ibid. 52, No. 4, 1867--1886 (2014; Zbl 1311.33006)], where we proposed an algorithmic approach for approximate calculation of sums of the form \(\sum_{j=1}^{N} f(j)\). The method is based on a Gaussian type quadrature formula for sums, which allows the calculation of sums with a very large number of terms \(N\) to be reduced to sums with a much smaller number of summands \(n\). In this paper we prove that the Weierstrass-Dochev-Durand-Kerner iterative numerical method, with explicitly given initial conditions, converges to the nodes of the quadrature formula. Several methods for computing the nodes of the discrete analogue of the Gaussian quadrature formula are compared. Since, for practical purposes, any approximation of a sum should use only the values of the summands \(f({j})\), we implement a simple but efficient procedure to additionally approximate the evaluations at the nodes by local natural splines. Explicit numerical examples are provided. Moreover, the error in different spaces of functions is analyzed rigorously.
monospline, Gaussian type quadrature formula for sums, 511, zeros of Gram polynomials, approximate calculation of sums, Numerical computation of roots of polynomial equations, Numerical integration, orthogonal Gram polynomials, Weierstrass-Dochev-Durand-Kerner method, 518, zeros of Legendre polynomials, natural spline, error analysis
monospline, Gaussian type quadrature formula for sums, 511, zeros of Gram polynomials, approximate calculation of sums, Numerical computation of roots of polynomial equations, Numerical integration, orthogonal Gram polynomials, Weierstrass-Dochev-Durand-Kerner method, 518, zeros of Legendre polynomials, natural spline, error analysis
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