随机抽样误差:参数曲线上均匀分布的随机点

Apostolos Chalkis, Christina Katsamaki, Josué Tonelli-Cueto
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引用次数: 1

摘要

给定一条参数多项式曲线γ:[a,b]→Rn,我们如何对一个随机点x∈im(γ)进行抽样,使其相对于弧长均匀分布?不幸的是,我们无法对这样一个点进行精确采样——即使假设我们可以进行精确的算术运算。因此,我们最终得到以下问题:我们选择的方法如何影响我们获得的近似样本的质量?在实践中,有很多答案。然而,从理论上讲,我们的理解仍然存在差距。在本文中,我们从复杂性理论的角度解决了这个问题,提供了期望误差大小的界限。
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On the Error of Random Sampling: Uniformly Distributed Random Points on Parametric Curves
Given a parametric polynomial curve γ:[a,b] →Rn, how can we sample a random point x ∈ im(γ) in such a way that it is distributed uniformly with respect to the arc-length? Unfortunately, we cannot sample exactly such a point---even assuming we can perform exact arithmetic operations. So we end up with the following question: how does the method we choose affect the quality of the approximate sample we obtain? In practice, there are many answers. However, in theory, there are still gaps in our understanding. In this paper, we address this question from the point of view of complexity theory, providing bounds in terms of the size of the desired error.
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