Examples of using Our vector in English and their translations into Arabic
{-}
-
Colloquial
-
Political
-
Ecclesiastic
-
Ecclesiastic
-
Computer
And this is our vector X.
If we draw our vector the length here is going to be 90.
That's that row times our vector.
That means that our vector x is the 0 vector, and only the 0 vector. .
So we will define A times our vector x.
We know already that our vector, our matrix, can be rewritten like this.
This is equal to a dot u, times our vector u.
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.
It was 1 over the square root of 5 times our vector v, right there.
Our vector u, our unit vector that defines this line, is equal to the vector 2 over the square root of 5 and 1 over the square root of 5.
Roger that.- What's our vector, Victor?
The unit vector is this,1 over the square root of 5 times our vector v.
Well that's just our matrix A times our vector-- or our matrix uppercase A.
We're going to define theta as the angle between the positive x-axis and our vector.
He brings a strong commitment to our Vector process and a keen sense of urgency to our business.
These are just arbitrary numbers depending on what our vector x is.
You can almost imagine F being the addition of our vector fields, P and Q, that we did in the last two videos.
So this is equal to the matrix capital Atimes a1, a2, all the way down to a n, which was our vector a.
Our vector drives allow you to push the spindle to 150 percent of the motor's continuous power rating for 15 minutes, and to 200 percent for 3 minutes.
It tells us this is less than or equal to the length of our vector a plus the length of minus b.
And just to make sure you understand the notation or the terminology,each of these is called a component of our vector.
So if we have minus 1/3 times this,the B coordinate representation of our vector x is going to be equal to minus 1 and then 1, just like that, which is actually interesting for this example.
We could say minus b,which would be in that direction plus a would give us our vector a minus b.
So just like that,you see that the transformation of c times our vector a, for any vector a in r2-- anything in r2 can be represented this way-- is the same thing as c times the transformation of a.
So it's fairly straightforward to prove that this is equal to c times our matrix a-- Iwill make that nice and bold, times our vector v.
A linear transformation of x, of our vector x, is the same thing as taking the linear transformation of this whole thing-- let me do it in another color-- is equal to the linear transformation of-- actually, instead of using L.
That's what ax can be rewritten as, as kind of a weighted combination of these columnvectors where the weights are each of the values of our vector x.
So if the derivative, the partial derivative, of this vector field with respect to y is increasing or decreasing, if it's just changing, that means as we increase in y, or as we decrease in y,the magnitude of the x-component of our vectors, right, the x-direction of our vectors changes.
And we could represent this linear transformation as being, we could say T2 applied to some vector xis equal to some transformation vector S2, times our vector x.
And I'm assuming that A is our transformation matrix, so we can write our transformationT as being equal to some matrix times our vector in our domain.
