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method of discretization in time and partial differential equations by Karel Rektorys

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Published by D. Reidel, Sold and distributed in the U.S.A. and Canada by Kluwer Boston Inc. in Dordrecht, Boston, Hingham, MA .
Written in English


  • Boundary value problems -- Numerical solutions.,
  • Differential equations, Parabolic -- Numerical solutions.,
  • Evolution equations -- Numerical solutions.

Book details:

Edition Notes

StatementKarel Rektorys.
SeriesMathematics and its applications. East European series ;, v. 4, Mathematics and its applications (D. Reidel Publishing Company), Mathematics and its applications (D. Reidel Publishing Company)., v. 4.
LC ClassificationsQA379 .R4413 1982
The Physical Object
Paginationxviii, 451 p. ;
Number of Pages451
ID Numbers
Open LibraryOL3488023M
ISBN 109027713421
LC Control Number82007658

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Finite difference methods for ordinary and partial differential equations: steady-state and time-dependent problems / Randall J. LeVeque. Includes bibliographical references and index. ISBN (alk. paper) 1. Finite differences. 2. Differential equations. I. . The Method of Discretization in Time and Partial Differential Equations (Mathematics and its Applications) Hardcover – Decem by K. Rektorys (Author) See all formats and editions Hide other formats and editions. Price New from Used from Cited by: Numerical Methods for Partial Differential Equations: Finite Difference and Finite Volume Methods focuses on two popular deterministic methods for solving partial differential equations (PDEs), namely finite difference and finite volume methods. The solution of PDEs can be very challenging, depending on the type of equation, the number of. The numerical solution of the reaction and diffusion equations of the system (7) is obtained by using the Euler finite difference approximations method for the discretization in time and space [

20 rows  LECTURE SLIDES LECTURE NOTES; Numerical Methods for Partial Differential Equations .   Discretization of partial differential equations (PDEs) is based on the theory of function approximation, with several key choices to be made: an integral equation formulation, or approximate solution operator; the type of discretization, defined by the function subspace in which the solution is approximated; the choice of grids, e.g. regular versus irregular grids to conform to the geometry. A new method for the acceleration of linear and nonlinear time-dependent calculations is presented. It is based on the large discretization step (LDS, in short) approximation, defined in this work, which employs an extended system of low accuracy schemes to approximate a high accuracy discrete approximation to a time-dependent differential by: 2. Numerical Methods for Partial Differential Equations is an international journal that aims to cover research into the development and analysis of new methods for the numerical solution of partial differential equations. Read the journal's full aims and scope. Supporting Authors. Numerical Methods for Partial Differential Equations supports.

Chapter 10 Advection Equations and Hyperbolic Systems Chapter 11 Mixed Equations Part III: Appendices. Chapter 12 Measuring Errors Chapter 13 Polynomial Interpolation and Orthogonal Polynomials Chapter 14 Eigenvalues and inner product norms Chapter 15 Matrix powers and exponentials Chapter 16 Partial Differential Equations.   A general method to discretize partial differential equations is to approximate the solution within a finite dimensional space of trial functions. 4 The partial differential equation is turned into a finite system of equations or a finite system of ordinary differential equations if time is treated as a continuous variable. This is the basis of spectral methods which make use of polynomials or Author: Philipp O. J. Scherer. The simplest approach to discretize a differential equation replaces differential quotients by quotients of finite differences. For the space variables this method works best on a regular grid. Finite volume methods, which are very popular in computational fluid dynamics, take averages over small control volumes and can be easily used with Author: Philipp O. J. Scherer. Numerical Solution of Partial Differential Equations—II: Synspade provides information pertinent to the fundamental aspects of partial differential equations. This book covers a variety of topics that range from mathematical numerical analysis to numerical methods applied to problems in mechanics, meteorology, and fluid dynamics.