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arXiv 2004.02342cs.DS
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基于k向量的非线性函数反演

Nonlinear Function Inversion using k-vector

David Arnas, Daniele Mortari

摘要:

这项工作介绍了一种通用的数值技术,以扭转一维解析或列表的非线性函数在指定的范围内的利益。所提出的方法是基于最佳版本的k-向量范围搜索,一个特设的修改设计的函数反演。最优性包括在指定的搜索范围内始终检索相同数量的数据($1,2,\dots$)以启动根求解器。这提供了使该技术适应各种根解算器(例如,二分法、牛顿法等),使用指定数量的起始点。所提出的方法允许建立一个反函数工具箱的一组指定的非线性函数。特别是,该方法是合适的,当需要密集的反演相同的功能。反演非常快(几乎是瞬时的),但它需要一次性的预处理工作。

英文摘要:

This work introduces a general numerical technique to invert one dimensional analytic or tabulated nonlinear functions in assigned ranges of interest. The proposed approach is based on an optimal version of the k-vector range searching, an ad-hoc modification devised for function inversion. The optimality consists of retrieving always the same number of data ($1,2,\dots$) for a specified searching range to initiate the root solver. This provides flexibility to adapt the technique to a variety of root solvers (e.g., bisection, Newton, etc.), using a specified number of starting points. The proposed method allows to build an inverse function toolbox for a set of specified nonlinear functions. In particular, the method is suitable when intensive inversions of the same function are required. The inversion is extremely fast (almost instantaneous), but it requires a one-time preprocessing effort.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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