Examples of using Our vector 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
So x plus minus 1 times our vector y.
This is our vector field plus yi plus xj.
I could have done 1.5 times our vector v.
And our vector field is going to be a little unusual;
That's that row times our vector.
If I do 2 times our vector, I'm going to get the vector 4, 2.
I could do 0.001 times our vector v.
So the transformation of our vector b is going to be-- b is just b1 b2-- so it's going to be b1 plus b2.
This is the definition of our vector field.
But we saw that if our vector field is the gradient of a scalar field then we call it conservative.
It is equal to minus 1, 0, 0, 2, times our vector.
And remember what our vector field was.
The base here is going to be the length of our vector v.
So the magnitude or the length of our vector x plus y squared can be rewritten like this.
T applied to T-inverse applied to c times our vector a.
So it's all the possible scalar multiples of our vector v where the scalar multiples, by definition, are just any real number.
By the same argument, what is the transformation of our vector b?
I guess that's a good place to start. c times our vector a is going to be equal to c times a1.
This is equal to some new matrix-- I will make it pretty big right here-- times our vector x.
Now, our y-coordinate is going to be determined by this part of our vector addition because these are the y-coordinates.
So this is equal to the matrix capital A times a1, a2, all the way down to a n,which was our vector a.
So what happens if we take t, so some scalar, times our vector, times the vectors b minus a?
Well, by our definition of our linear, of our composition, this is equal to the transformation T applied to the transformation S, applied to c times our vector x.
It tells us this is less than or equal to the length of our vector a plus the length of minus b.
Well, if we factor the x-component, that's the same thing as, we could rewrite our vector field.
And so the divergence-- I will use this notation-- the divergence of our vector field is just a partial derivative with respect to x, which is just minus 1/2.
The correct way to write it is the divergence of our vector field, v.
So all the points on the curve where we care about, this is our vector field, that is our vector field.
So div of v is the same thing as our del operator dot our vector field, v.
So it makes sense, if our partial derivatives are positive, that means that the magnitude of our vector is getting larger and larger for larger values of our x's and y's.