Examples of using This vector right here in English and their translations into Thai
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Colloquial
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Ecclesiastic
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Ecclesiastic
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Computer
I get this vector right here.
It's going to be perpendicular to this vector right here.
Av times this vector right here.
So if we just rotate x first, we're going to get this vector right here.
You get this vector right here, 3, 0.
We figured out that the rank of this vector right here is 1.
So A times this vector right here is indeed equal to b.
The point specified by this vector right here.
So this vector right here is the vector x plus y.
Our transformation of x1 is this vector right here in R2.
Similarly, this vector right here-- I hope you can see it.
Well this is all of the linear combinations of this vector right here.
So this vector right here, by our function, f, got mapped.
The dot product of n with this vector right here-- actually.
Likewise, this vector right here has a 1 in the fourth position.
We learned in, I think it was the previous video, that b minus a, you will get this vector right here.
So this vector right here is just going to be the vector 1, 0, 0.
T applied to two separate vectors-- so we call this one vector right here, and this vector right here.
And so r of a will be this vector right here that ends at that point.
This vector right here in r3 got mapped to this vector in r2 by our function.
So you could take Ax, that's a vector, and now we are dotting it with this vector right here and we will get a number.
So this vector right here is the rotation by an angle of theta counterclockwise of c, x.
When you add two vectors, you're adding, let me make it very clear, I'm adding this vector to this vector right here.
So this vector right here that has its endpoint right there-- its endpoint sits on that line.
What matters is that the same number of A's you have in this direction, you have n A's here, then you have n components of this vector right here.
We're taking this vector right here, dotting it with v, and we know that this has to be equal to 0.
Then I can write this product as just the dot products of each of these transpose, or I guess you could say the inverse transpose, with this vector right here.
So if you think about it, this vector right here, if you imagine this is a position factor, this is velocity.
But the bottom line, this vector right here-- if you add these scaled values of these two unit vectors, you're going to get r of a looking something like this. it's going to be a vector that looks something like that.
So if you were to rotate this vector right here, this blue vector right here, by an angle of theta, it will look like this. .