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arXiv 0812.0387cs.CGcs.DS
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线性时间中的德洛内三角剖分(Part第一章)

Delaunay Triangulations in Linear Time? (Part I)

Kevin Buchin

摘要:

本文提出了一种新的、简单的随机算法,利用最近邻图构造德洛内三角剖分进行点定位。在适当的假设下,它在线性期望时间内运行,平面上的点具有多项式有界的扩展,即,如果最大和最小逐点距离之间的比率是多项式有界的。这也适用于在更高维度中具有有界扩展的点集,只要点的样本的德洛内三角剖分的预期复杂度在样本大小中是线性的。

英文摘要:

We present a new and simple randomized algorithm for constructing the Delaunay triangulation using nearest neighbor graphs for point location. Under suitable assumptions, it runs in linear expected time for points in the plane with polynomially bounded spread, i.e., if the ratio between the largest and smallest pointwise distance is polynomially bounded. This also holds for point sets with bounded spread in higher dimensions as long as the expected complexity of the Delaunay triangulation of a sample of the points is linear in the sample size.

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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