图灵机的时间复杂度与空间复杂度

发布于 2024-11-30 18:43:51 字数 60 浏览 6 评论 0原文

我认为图灵机的时间复杂度和空间复杂度的定义是相同的,我无法区分 他们之间。

请帮我。谢谢。

I think defenitions of time complexity and space complexity for Turing machines are identical and I can't differentiate
between them.

Please help me. Thanks.

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南七夏 2024-12-07 18:43:51

对于图灵机,时间复杂度是当机器根据某些输入启动时磁带移动的次数的度量。空间复杂度是指机器运行时写入磁带的单元数。

TM 的时间复杂度与其空间复杂度相关。特别是,如果对于输入 w,TM 的空间复杂度为 f(w),那么它的时间复杂度必须至少为 f(w),因为磁带必须移动至少 f(w) 步才能写出这么多细胞。此外,如果 TM 具有磁带字母 Γ 和状态集 Q,则如果 TM 在输入 w 上的空间复杂度为 f(w) 并且 TM 在 w 上停止,则时间复杂度必须至多为 f(n) |Q|Гf(n)。要看到这一点,请注意 TM 在其执行过程中任何点的配置都由一串 f(n) 个磁带单元组成,每个磁带单元都可以包含任何磁带符号,并且可以位于其任何 |Q| 之一中。磁头处于任何 f(n) 位置的状态。

如果您查看像线性有界自动机这样的受限图灵机,就会出现这种区别的一个有趣的例子( LBA),一种图灵机,其磁带受限于与输入大小成比例的空间。尽管 TM 的空间复杂度限制为 O(n),但任何特定 LBA 的时间复杂度都可以是输入大小的指数。

希望这有帮助!

With regards to a Turing machine, time complexity is a measure of how many times the tape moves when the machine is started on some input. Space complexity refers to how many cells of the tape are written to when the machine runs.

The time complexity of a TM is connected to its space complexity. In particular, if tue space complexity of a TM is f(w) for input w, then its time complexity must be at least f(w), since the tape has to move at least f(w) steps to write out that many cells. Additionally, if the TM has tape alphabet Γ and set of states Q, then if the space complexity of the TM on an input w is f(w) and the TM halts on w, the time complexity must be at most f(n)|Q|Γf(n). To see this, note that the configuration of the TM at any point in its execution consists of a string of f(n) tape cells, each of which can contain any tape symbol, and can be in one of any of its |Q| states with the tape head in any of the f(n) positions.

An interesting example of this distinction appears if you look at restricted Turing machines like the linear bounded automaton (LBA), a Turing machine that has its tape restricted to space proportional to the size of the input. Although the TM's space complexity is restricted to O(n), the time complexity of any particular LBA can be exponential in the size of the input.

Hope this helps!

尸血腥色 2024-12-07 18:43:51

时间复杂度是衡量算法产生答案所需的时间

空间复杂度是算法在该过程中使用内存量的度量。

例如,考虑计算整数 1..n 之和的问题。一个简单的算法的工作原理如下:

procedure sum(n)
  total := 0
  for i = 1 to n
    total := total + a[n]
  return total

该算法的时间复杂度为 O(n),因为循环明显经历了 n 次迭代。另一方面,空间复杂度为 O(1),因为我们唯一需要的内存是 totali,它们独立于 n >。

Time complexity is the measure of how long the algorithm takes to produce an answer.

Space complexity is the measure of how of much memory the algorithm uses in the process.

As an example, consider the problem of computing the sum of the integers 1..n. A simple algorithm would work something like:

procedure sum(n)
  total := 0
  for i = 1 to n
    total := total + a[n]
  return total

The time complexity of this algorithm is O(n) because the loop clearly goes through n iterations. On the other hand, the space complexity is O(1) because the only memory we need is for total and i, which are independent of n.

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