The Abel-type polynomial identities.
Huang, Fengying, Liu, Bolian (2010)
The Electronic Journal of Combinatorics [electronic only]
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Displaying similar documents to “A full discretization of the time-dependent Navier-Stokes equations by a two-grid scheme”
The Abel-type polynomial identities.
Extensions of the results on powers of -hyponormal and -hyponormal operators.
Yang, Changsen, Yuan, Jiangtao (2006)
Journal of Inequalities and Applications [electronic only]
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Arcangeli's type discrepancy principles for a class of regularization methods using a modified projection scheme.
Nair, M.T., Rajan, M.P. (2001)
Abstract and Applied Analysis
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A self-indexed sequence.
Preissmann, Emmanuel (2005)
Journal of Integer Sequences [electronic only]
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A posteriori error analysis of the fully discretized time-dependent Stokes equations
Christine Bernardi, Rüdiger Verfürth (2004)
ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique
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The time-dependent Stokes equations in two- or three-dimensional bounded domains are discretized by the backward Euler scheme in time and finite elements in space. The error of this discretization is bounded globally from above and locally from below by the sum of two types of computable error indicators, the first one being linked to the time discretization and the second one to the space discretization.
Strong and weak order of time discretization schemes of stochastic differential equations
Yao-Zhong Hu (1996)
Séminaire de probabilités de Strasbourg
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Error estimates for finite volume scheme for Perona--Malik equation.
Handlovičová, A., Krivá, Z. (2005)
Acta Mathematica Universitatis Comenianae. New Series
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Some remarks on numerical solution of initial problems for systems of differential equations
Tadeusz Jankowski (1979)
Aplikace matematiky
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This paper presents a class of numerical methods for approximate solution of systems of ordinary differential equations. It is shown that under certain general conditions these methods are convergent for sufficiently small step size. We give estimations of errors which are better than the known ones.