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引用次数: 57

摘要

在本文中,我们描述了一个计算初值问题(IVP)解的保证界的新库。给定一个初值问题和一个终点,我们的库计算一系列近似点和一系列近似误差,使得在每个近似点到IVP真解的距离低于这些误差项。这些序列是使用经典的龙格-库塔方法计算的,该方法可能会过度逼近截断和舍入误差。我们还计算了局部误差的传播,以便在每个计算步骤中得到全局误差的一个框图。这些技术是在一个c++库中实现的,该库为IVP的严格逼近提供了一个易于使用的框架。为了达到一定的局部误差容忍度,该库实现了一种基于步长缩减的误差控制技术。
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GRKLib: a Guaranteed Runge Kutta Library
In this article, we describe a new library for computing guaranteed bounds of the solutions of Initial Value Problems (IVP). Given an initial value problem and an end point, our library computes a sequence of approximation points together with a sequence of approximation errors such that the distance to the true solution of the IVP is below these error terms at each approximation point. These sequences are computed using a classical Runge-Kutta method for which truncation and roundoff errors may be over-approximated. We also compute the propagation of local errors to obtain an enclosure of the global error at each computation step. These techniques are implemented in a C++ library which provides an easy-to-use framework for the rigorous approximation of IVP. This library implements an error control technique based on step size reduction in order to reach a certain tolerance on local errors.
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