But when I read how they described it to each other, talking about eigenvalues and

但当我读到他们彼此描述时，讨论特征值及各种数学术语，些内容变得有意义了。

If you actually try computing the eigen values of a rotation like this, notice what happens.

如果你试着计算像旋转特征值 注意会发生什么。

And if for your question, it's necessary to really compile these traits values into categories, then you can do that.

而且如果为了你问题， 确实需要将些特征值归类，那么你可以。

It is not an easy read, but one that readers who are undeterred by having to learn about “eigenvalues” or “asymptotic freedom” will find intellectually gratifying.

看懂本书不容易，但不畏了解什么“特征值”或“渐近自由”读者会发现本书让人有智成就感。

All of the vectors on the x axis are eigen vectors with eigen valued one, since they remain fixed in place.

x轴所有向量都特征值为1特征向量 因为它们保持固定。

Of course, there's nothing special about stretching versus squishing, or the fact that these eigen values happen to be positive.

当然 拉伸和挤压并没有什么特别 或者说些特征值恰好正。

The only eigen value is two, but every vector in the plane gets to be an eigenvector with that eigen value.

唯一特征值2 但平面每个向量都具有个特征值特征向量。

These experts can recognize different moths, so they not only record the feature values, but also label that data with the actual moth species.

些专家能够识别不同飞蛾， 因此他们不仅记录特征值，还会用实际飞蛾种类来标注些数据。

A is the matrix representing some transformation with V as the icon vector, and lambda is a number, namely the corresponding eigen value.

A表示以V为图标向量某个变换矩阵 lambda一个数字 即对应特征值。

Confusion about agon stuffs usually has more to do with the shaky foundation in one of these topics than it does with eigenvectors and eigen values themselves.

对正交困惑通常更多与些主题中一个不稳定基础有关 而不与特征向量和特征值本身有关。

And the way to interpret this is that all the basis vectors are eigenvectors, with the diagonal entries of this matrix being their eigen values.

解释个方法所有基向量都特征向量 个矩阵对角线元素它们特征值。

So finding the eigen vectors and their eigen values of the matrix A comes down to finding the values of V and lambda that make this expression true.

所以求出矩阵A特征向量和它们特征值归结为求出V和使个表达式成立值。

For those of you wondering why we care about alternate coordinate systems, the next video on eigen vectors and eigen values, we'll give a really important example of this.

对于那些想知道为什么我们要关心交替坐标系人 下一集关于特征向量和特征值视频 我们会给出一个很重要例子。

In this case, by the way, the corresponding eigen value would have to be one, since rotations never stretcher squish anything, so the length of the vector would remain the same.

顺便说一下 在种情况下 对应特征值必须1 因为旋转不会拉伸压扁任何东西 所以向量长度保持不变。