文件名称:MinDistance
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算法的步骤如下:
1.找出Sx的中位数:median_Sx;用median_Sx对点集S进行划分,左边的为S1,右边的为S2;
2.分别求出S1和S2中的最近点对,设S1和S2中最近点对的距离分别为:delta(S1), delta(S2);
T(n)= 2*T(n/2)+O(n). 由主定理,可知T(n) = O(n*log(n));(The steps of the algorithm are as follows:
1., find out the median of Sx: median_Sx; use median_Sx to divide the point set S; the left side is S1, and the S2 on the right is S2.
T (n) = 2*T (n/2) + merge complexity. When merging, it is compared with the n/2 points in S1 and the most 6 points in S2. The number of comparisons is n/2 * 6 = 3n..
T (n) = 2*T (n/2) +O (n). From the main theorem, we know T (n) = O (n*log (n)).)
1.找出Sx的中位数:median_Sx;用median_Sx对点集S进行划分,左边的为S1,右边的为S2;
2.分别求出S1和S2中的最近点对,设S1和S2中最近点对的距离分别为:delta(S1), delta(S2);
T(n)= 2*T(n/2)+O(n). 由主定理,可知T(n) = O(n*log(n));(The steps of the algorithm are as follows:
1., find out the median of Sx: median_Sx; use median_Sx to divide the point set S; the left side is S1, and the S2 on the right is S2.
T (n) = 2*T (n/2) + merge complexity. When merging, it is compared with the n/2 points in S1 and the most 6 points in S2. The number of comparisons is n/2 * 6 = 3n..
T (n) = 2*T (n/2) +O (n). From the main theorem, we know T (n) = O (n*log (n)).)
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新建文本文档 (3).txt | 8852 | 2018-04-11 |
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