So let's actually let you try another example of solving a problem that has to do with one of the spectrums.
下面请大家来看一下另一个例子,这次是一个需要大家解决的关于光谱的问题。
For example, if you're discussing a problem with a friend. Perhaps a marital problem.
例如,假设你跟朋友在讨论一个问题。可能是婚姻问题。
Using the example of Star Trek, Steven Pinker, in his book How the Mind Works, nicely illustrates the problem here.
用星际迷航举例,史蒂芬,朋克,在中,精细地列出了问题。
I'm thinking about a problem, I'm going to show you an example in a second, first thing I'm going to do is say, what is the thing that's going to change every time I run through the same set of code?
我要解决一个问题,我马上会让大家看一个例子,第一件我要做的事情就是,弄明白每次运行同样的指令集时,每次都会改变的东西是什么?
Here's a simple example of a complete Newtonian problem.
这里是一个牛顿力学问题的简单例子
If you see a problem that asks you, for example, the third ionization energy versus taking a second electron out of the 2 s in a photoelectron spectroscopy experiment, those are two very different things.
如果你遇到一个题目问你的是,比如说,是第三电离能,还是在光电子能谱实验中从,2,s,轨道中,拿走第二个电子,这可是两个完全不同的问题。
Not so easy to see. All right, but this is actually a great one of those educational moments. This is a great example to think recursively. If I wanted to think about this problem recursively- what do I mean by thinking recursively?
看不太出来,好,但实际上是一个有教育意义的时刻,这是一个很好的关于递归的例子,如果我用递归的思想,去考虑这个问题-,我该怎么用递归去解决这个问题呢?
Now that--If the only language you've ever heard is English, that's going to seem like a really weird example of a problem because you're listening to me speak and in between each of my words you're hearing a pause.
如果你只接触过英语,那么刚才的问题就看上去非常奇怪了,因为你在听我讲话,而你会在我所说的单词之间听到一个停顿
Typical characterization, not all the time, but typical characterization, is an algorithm that reduces the size of a problem by one, or by some constant amount each time, is typically an example of a linear algorithm.
我们学习过了线性算法,它的典型特征,不是通用的,但是比较典型的特征是,它是逐一减小问题的大小的,或者说是每次减小常数的大小。
This is an example of a problem called Towers of Hanoi. Anybody heard about this problem?
有人听说过么?,几个尝试性的举手?
So let's look at an example of a zero-one knapsack problem.
我们要像之前一样将其最优化,现在让我们来看一个0/1背包问题的例子。
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