我在Reddit上读到jng的一篇精彩的解释，用里程表做类比。

It is a useful convention. The same circuits and logic operations that add / subtract positive numbers in binary still work on both positive and negative numbers if using the convention, that's why it's so useful and omnipresent. Imagine the odometer of a car, it rolls around at (say) 99999. If you increment 00000 you get 00001. If you decrement 00000, you get 99999 (due to the roll-around). If you add one back to 99999 it goes back to 00000. So it's useful to decide that 99999 represents -1. Likewise, it is very useful to decide that 99998 represents -2, and so on. You have to stop somewhere, and also by convention, the top half of the numbers are deemed to be negative (50000-99999), and the bottom half positive just stand for themselves (00000-49999). As a result, the top digit being 5-9 means the represented number is negative, and it being 0-4 means the represented is positive - exactly the same as the top bit representing sign in a two's complement binary number. Understanding this was hard for me too. Once I got it and went back to re-read the books articles and explanations (there was no internet back then), it turned out a lot of those describing it didn't really understand it. I did write a book teaching assembly language after that (which did sell quite well for 10 years).

通过对给定数的第1个补数加1，可以求出两个补数。 假设我们要求出10101的两个补，然后求出它的一个补，也就是，在这个结果上加1，也就是，01010+1=01011，这就是最终答案。

到目前为止，许多答案都很好地解释了为什么2的补数被用来表示负数，但没有告诉我们2的补数是什么，尤其是没有告诉我们为什么加了一个“1”，而且实际上经常以错误的方式加。

这种混淆来自于对补数定义的不理解。补语是指使某物完整的缺失部分。

根据定义，n位数x以b为基数的基数补是b^n-x。

在二进制中，4由100表示，它有3位数字(n=3)和基数2 (b=2)。所以它的基数补是b^n-x = 2^3-4=8-4=4(或二进制的100)。

然而，在二进制中，求一个基数的补并不像求它的消简基数补那么容易，消简基数补定义为(b^n-1)-y，只比基数补小1。要得到一个减少的基数补，只需翻转所有的数字。

100 -> 011(减基数补位)

为了得到基数(2的)补，我们只需按定义加1。

011 +1 ->100(2的补码)。

现在，有了这个新的理解，让我们看看Vincent Ramdhanie给出的例子(见上面的第二个回答):

将1111转换为十进制: 这个数从1开始，所以它是负的，所以我们找到1111的补数，也就是0000。 0000加上1，得到0001。 将0001转换为十进制，即1。 应用符号= -1。 大作。

应理解为:

数字从1开始，所以是负的。所以我们知道它是x的一个2的补。为了找到由它的2的补表示的x，我们首先需要找到它的1的补。

x的2的补数是1111 x的补数:1111-1 ->1110; X = 0001，(翻转所有数字)

应用符号-，结果=-x =-1。

2对给定数的补数是1与1的补数相加得到的数。

假设我们有一个二进制数:10111001101

它的1的补位是:01000110010

它的2的补数是:01000110011

想象一下，你有有限数量的比特/比特/数字等等。将0定义为所有数字都为0，并自然向上计数:

00
01
02
..

最终你会溢出。

98
99
00

我们有两位数字，可以表示从0到100的所有数字。所有这些数字都是正数!假设我们也想表示负数?

我们真正拥有的是一个循环。2之前的数字是1。1之前的数字是0。0之前的数字是…99.

为了简单起见，我们设任何大于50的数都是负数。0 ~ 49代表0 ~ 49。“99”是-1，“98”是-2，…“50”是-50。

这个表示是十的补数。计算机通常使用2的补码，除了使用位而不是数字之外，它是一样的。

10的补数的好处在于加法运算可以正常进行。你不需要做任何特殊的加法和负数!

2's complement is essentially a way of coming up with the additive inverse of a binary number. Ask yourself this: Given a number in binary form (present at a fixed length memory location), what bit pattern, when added to the original number (at the fixed length memory location), would make the result all zeros ? (at the same fixed length memory location). If we could come up with this bit pattern then that bit pattern would be the -ve representation (additive inverse) of the original number; as by definition adding a number to its additive inverse always results in zero. Example: take 5 which is 101 present inside a single 8 bit byte. Now the task is to come up with a bit pattern which when added to the given bit pattern (00000101) would result in all zeros at the memory location which is used to hold this 5 i.e. all 8 bits of the byte should be zero. To do that, start from the right most bit of 101 and for each individual bit, again ask the same question: What bit should I add to the current bit to make the result zero ? continue doing that taking in account the usual carry over. After we are done with the 3 right most places (the digits that define the original number without regard to the leading zeros) the last carry goes in the bit pattern of the additive inverse. Furthermore, since we are holding in the original number in a single 8 bit byte, all other leading bits in the additive inverse should also be 1's so that (and this is important) when the computer adds "the number" (represented using the 8 bit pattern) and its additive inverse using "that" storage type (a byte) the result in that byte would be all zeros.

 1 1 1
 ----------
   1 0 1
 1 0 1 1 ---> additive inverse
  ---------
   0 0 0