1978
DOI: 10.2307/2006328
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Symbolic Generation of Finite Difference Formulas

Abstract: Abstract. Tables of coefficients for high order accurate, compact approximations to the first ten derivatives on and at the midpoints of uniform nets are presented.The exactrational weights are generated and tested by means of symbolic manipulation implemented through MACSYMA. These weights are required in the application of deferred corrections to new methods for solving higher order two point boundary value problems.1. Introduction. Compact difference schemes are, by definition, those which use the least num… Show more

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Cited by 8 publications
(7 citation statements)
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“…, x N ) that depends only on x 1 . Application of S then results in a one-dimensional finite-difference scheme for which it is known that its coefficients have alternating sign [3]. For r > 1, this violates the assumption of diagonal dominance as there all coefficients (except for the one in the centre) have the same sign [cf.…”
Section: The Most General Form Of a Partial Differential Equation (Pdmentioning
confidence: 99%
“…, x N ) that depends only on x 1 . Application of S then results in a one-dimensional finite-difference scheme for which it is known that its coefficients have alternating sign [3]. For r > 1, this violates the assumption of diagonal dominance as there all coefficients (except for the one in the centre) have the same sign [cf.…”
Section: The Most General Form Of a Partial Differential Equation (Pdmentioning
confidence: 99%
“…The most ambitious attempt to tabulate weights for many orders of derivatives and to high orders of accuracy appears to be the work by Keller and Pereyra [4]. However, their algorithms (limited to equispaced grids) were very involved, and the resulting tables contain both isolated and systematic errors.…”
Section: Introductionmentioning
confidence: 99%
“…The coefficients ctij in (12) For the practical computation of the coefficients c%, see [9]. .jeS2 (20) Proof Recalling the definition of C k in (12), result (19a) follows from (16).…”
Section: High-order Diseretizationsmentioning
confidence: 99%