An engineering expose of numerical integration of ordinary differential equations
Error analyses for numerically integrating first order ordinary differential equations
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Error analyses for numerically integrating first order ordinary differential equations
Ascent existence and uniqueness proof for linear ordinary differential equations
Existence theorems for solutions to second order ordinary differential equations
Series of computer subroutines integrates systems of ordinary differential equations and is used for numerical quadrature.
Reference list for stability and control theory in ordinary differential equations
Self-starting multistep methods for numerical integration of ordinary differential equations
Chebyshev series solution of nonlinear ordinary differential equations - initial value problems
Relative and absolute stability regions determined for numerical solutions of ordinary differential equations
Operational unification of finite difference methods for numerical integration of ordinary differential equations
Explicit numerical methods for integrating coupled nonlinear ordinary differential equations with parasitic eignevalues
Accelerating convergence of one step methods for numerical solution of ordinary differential equations, discussing various initial value problems
New methods for integrating systems of stiff, nonlinear, first order, ordinary differential equations are developed by casting the differential equations into integral form. Nonlinear recursive relations are obtained that allow the solution to a system of equations at time t plus delta t to be obtained in terms of the solution at time t in explicit and implicit forms. Examples of accuracy obtained with the new technique are given by considering systems of nonlinear, first order equations which arise in the study of unified models of viscoplastic behaviors, the spread of the AIDS virus, and predator-prey populations. In general, the new implicit algorithm is unconditionally stable, and has a Jacobian of smaller dimension than that which is acquired by current implicit methods, such as the Euler backward difference algorithm; yet, it gives superior accuracy. The asymptotic explicit and implicit algorithms are suitable for solutions that are of the growing and decaying exponential kinds, respectively, whilst the implicit Euler-Maclaurin algorithm is superior when the solution oscillates, i.e., when there are regions in which both growing and decaying exponential solutions exist.
The equivalence of a considered integral equation form with an infinite system of linear equations is proved, and the localization of the eigenvalues of the infinite system is expressed. Error estimates are derived, and the problems of finding upper bounds and lower bounds for the eigenvalues are solved simultaneously.
Variable mesh multistep predictor-corrector method for iterative solution of ordinary differential equations, considering numerical stability and algorithm efficiency
A program for the solution of linear and nonlinear first order ordinary differential equations is described and user instructions are included. The program contains a new integration algorithm for the solution of initial value problems which is particularly efficient for the solution of differential equations with a wide range of eigenvalues. The program in its present form handles up to ten state variables, but expansion to handle up to fifty state variables is being investigated.
Recently the determination of the best technique for numerically solving systems of ordinary differential equations on a digital computer has received much attention. The use of these formulas in conjunction with a stepsize control developed is explained, and one of the formulas is chosen for comparison with other integration techniques. This comparison of one of the best of Fehlberg's formulas with the different numerical techniques described in previous studies on a variety of test problems clearly shows the superiority of Fehlberg's formula. That is, on each of the test problems, the chosen Fehlberg formula is able to achieve a given accuracy in less computer time than any of the other techniques tested. Also, the computer program for the chosen Fehlberg formula is less complex and easier to use than the computer programs for most of the other techniques. To illustrate the use of the chosen Fehlberg formula, a computer listing of its application to several example problems is included along with a sample of the computer output from these applications.
Difference methods for asymptotic estimates of errors at numerical integration of systems of ordinary differential equations
This paper discusses how to numerically test a subroutine for the solution of ordinary differential equations. Results obtained with a variable order Adams method are given for eleven simple test cases.-