• Let's do selection and let's do merge sort here on the right just to see what actually happens.

    中间进行选择排序,右边进行归并排序,看看会发生什么。

    哈佛公开课 - 计算机科学课程节选

  • Run merge sort on those. By induction, if it does the right thing, I'm going to get back two lists, and I'm going to then merge Them together. Notice what I'm going to do.

    在这些上面再运行归并排序,根据归纳,如果这样是正确的,我将重新得到两个列表,然后我会把它们合并在一起。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • It at least does corroborate the claim that merge sort N*log N as we argue intuitively is in fact, N log N in running time.

    但这至少证实了归并排序,的时间复杂度为。

    哈佛公开课 - 计算机科学课程节选

  • I hope you can see this because I'm going to try and simulate what a merge sort does. I've got eight things I want to sort here, and those initially start out here at top level.

    我希望你们认真看,因为我要尝试着模拟出归并排序的操作过程,这里我有八个元素进行排序,第一步是将它们分成两半,对吗?

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • Merge sort takes this idea of divide and conquer, and it does the following: it says let's divide the list in half.

    归并排序以如下的步骤使用了分治思想:,把列表分成两半:,下面就是分治。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • Well, we saw the teaser in terms of that animation that suggests this merge sort algorithm when implemented by a computer is absolutely faster.

    我们从前面的动画中可以看到,这个归并排序算法在计算机上实现之后,绝对比其他算法更快。

    哈佛公开课 - 计算机科学课程节选

  • OK, what I would like you to see is I've been printing out, as I went along, actually let's back up slightly and look at the code. There's merge sort.

    好的,我想让你们看就是我运行过后,打印出来的结果,我们再回头看一下这段代码,这就是归并排序,输入一个列表。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • So here's what merge sort would do.

    是归并排序的处理过程。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • I chose Bubble Sort on the left Selection Sort on the right and then something called merge sort on the very right hand side and then I started this all off roughly at the same time and what was frankly striking at least to me at the time was, my God it's done.

    我在左边选择冒泡排序,在中间选选择排序,在最右边选择归并排序,然后同时将它们启动,在那时,至少我是震惊了,天哪,它已经完成了。

    哈佛公开课 - 计算机科学课程节选

  • If I'm using algorithm that I'm now calling merge sort, T the running time involved in sorting N elements, T of N, you know, is just the same as running the algorithm for the right half, plus what's this plus N come from?

    如果我用归并排序算法,对N个元素其运行时间,就等于此算法一半元素的运行时间,另一半的运行时间,再加上N,这个N是什么呢?

    哈佛公开课 - 计算机科学课程节选

  • I'm gonna tell you go sort the left, go sort the right, and then I'll merge the two together.

    那先对左半部分排序,再对右半部分排序,然后将两者合并起来。

    哈佛公开课 - 计算机科学课程节选

  • Let's run merge sort on it, and then we'll look at the code.

    让我们在这个列表上运行归并排序,然后我们在看一下代码。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • - So again, if you're unwinding what's going on here, this-- we sorted the left half which meant sort the left half, then the right half then the merge.

    同样,如果你展开正在进行的一切-,我们已对左半部分排好了序,接着右半部分,接着合并。

    哈佛公开课 - 计算机科学课程节选

  • Wow I can sort two lists, so I can merge two lists.

    喔,我可以,将两个列表排好序。

    麻省理工公开课 - 计算机科学及编程导论课程节选

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