I experience a vector quantity.
我经历了一个矢量的量变。
So, in fact, it's a vector field.
事实上，是一个向量场。
一个与半径垂直的矢量。
That was a vector field in the plane.
它是一个在平面上的向量场。
它构成一个矢量。
We all have seen... this is a vector.
我们都见过…这就是矢量。
Remember this-- this is a vector.
记住它，这是个矢量。
有一个矢量。
Well, at the time, it was just a vector.
那时候，它只是一个向量。
That is called the curl of a vector field.
这个量叫向量场的旋度。
And we call that "decomposition" of a vector.
这就叫做矢量分解。
OK, so you take the divergence of a vector field.
取一个向量场的散度。
Such input can be viewed as a vector: <X1, X2, ...
这样的输入可以看成一个向量：<X 1,X 2, ...
And, the direction is essentially that of a vector.
方向基本和这里的单位切向量一致。
I have a curve in the plane and I have a vector field.
这有一条平面曲线和一个向量场。
We had a curve in the plane and we had a vector field.
平面上有一曲线，且存在着向量场。
A set of server binding handles is called a vector.
一组服务器绑定句柄称为向量。
I have a vector which is in three-dimensional space.
假设有一矢量，在三维空间中。
It measures how much a vector field goes across the curve.
它度量有多少向量场穿过了曲线。
It is a vector field in some of the flux things and so on.
也可以是一个向量场的通量，等等。
That actually is what we will call later a vector field.
这就是后面我们要讲的向量空间。
We have a vector field that gives us a vector at every point.
有一个向量场来描述每一个点上的向量。
This is a vector and that will be our representation of vectors.
这就是矢量，这就是矢量的，表示方法。
We need, actually, a vector field that is well-defined everywhere.
实际上我们需要，一个处处有定义的向量场。
Conversely, to double a vector image, you simply draw larger shapes.
反过来讲，要将矢量图像放大两倍，您只需要绘制更大的形状就可以了。
That means actually we should use a vector maybe to think about this.
这意味着，我们也许需要一个矢量来表示它。
Now, it's our first time writing this kind of thing with a vector.
这是我们第一次这样写一个矢量。
We are just integrating a vector field that has nothing to do with that.
其实是要对一个与其无关的向量场积分，其实是要对一个与其无关的向量场积分。
It's a vector field that just rotates around the origin counterclockwise.
这是一个绕原点逆时针旋转的向量场。
And, these coefficients here correspond to a vector parallel to the line.
这些系数构成的向量和直线平行。
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