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On an New Algorithm for Function Approximation with Full Accuracy in the Presence of Discontinuities Based on the Immersed Interface Method

机译:基于浸入接口方法的不连续性下具有全精度的函数逼近新算法

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This paper is devoted to the construction and analysis of an adapted and nonlinear multiresolution algorithm designed for interpolation or approximation of discontinuous univariate functions. The adaption attained allows to avoid numerical artifacts that appear when using linear algorithms and, at the same time, to obtain a high order of accuracy close to the singularities. It is known that linear algorithms are stable and convergent for smooth functions, but diffusion and Gibbs effect appear if the functions are piecewise continuous. Our aim is to develop an algorithm for function approximation with full accuracy that is capable to adapt to corners (kinks) and jump discontinuities, that uses a centered stencil and that does not use extrapolation. In order to reach this goal, we will need some information about the jumps in the function that we want to approximate and its derivatives. If this information is available, the algorithm is the most compact possible in the sense that the stencil is fixed and we do not need a stencil selection procedure as other algorithms do, such as ENO subcell resolution (ENO-SR). If the information about the jumps is not available, we will show a technique to approximate it. The algorithm is based on linear interpolation plus correction terms that provide the desired accuracy close to corners or jump discontinuities.
机译:本文致力于构造和分析一种自适应的非线性多分辨率算法,该算法设计用于对不连续单变量函数进行插值或逼近。达到的适应性可以避免使用线性算法时出现的数字假象,并同时获得接近奇异点的高精确度。众所周知,线性算法对于平滑函数是稳定且收敛的,但是如果函数是分段连续的,则会出现扩散和吉布斯效应。我们的目标是开发一种具有完全准确度的函数逼近算法,该算法能够适应拐角(扭结)和跳跃不连续性,并且使用居中的模板并且不使用外推法。为了实现此目标,我们将需要一些有关我们要近似的函数及其派生的跳跃的信息。如果此信息可用,则在模板固定的意义上,该算法是最紧凑的,并且我们不需要像其他算法那样需要模板选择过程,例如ENO子单元分辨率(ENO-SR)。如果没有有关跳跃的信息,我们将展示一种近似的技术。该算法基于线性插值加校正项,可提供接近拐角或跳跃不连续点的所需精度。

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