Examples of using Some vector in English and their translations into Arabic
{-}
-
Colloquial
-
Political
-
Ecclesiastic
-
Ecclesiastic
-
Computer
Plus x5 times some vector.
If I have some vector v that looks like that.
The free variables are x2 times some vector right there.
T of some vector x is equal to this matrix, B times that vector x.
What I could do is I could define some vector, let's call it U1.
Learning about some vector basics and how we can begin to operate in Adobe.
A, I have written this as general as possible, with some vector x.
When it's applied to some vector x, it's equivalent to multiplying that vector x times the matrix z.
If you add this guyplus 2 times that, you will get some vector up here.
We know that if I take some vector, and I dot it with itself, that is equivalent to the length of the vector squared.
So this transformation, it's entire domain is R2, so let's start with some vector x.
Well, the most obvious vector would be some vector that is orthogonal to V1.
So the transformation of some vector x is the reflection of x around or across, or however you want to describe it, around line L, around L.
So I can goback to what I was doing before. x5 times some vector right here.
So, if I have some vector-- let me write it as a lowercase a, but it's a really bolded lowercase a, and then that is equal to a1, a2.
If the imported image is the background layer,it can be difficult to delete it in some vector applications.
Modern processor instruction sets do include some vector processing instructions, such as with AltiVec and Streaming SIMD Extensions(SSE).
What I want to do in this video is verify that D actually works,that I could start with some vector x-- let me write it up here.
Now these guys over here, if you have some vector in this eigenspace that corresponds to lambda is equal to 3, and you apply the transformation.
And just to give you an example like that,if I wrote minus 3 times some vector-- I will just draw the vector here.
In particular, if we say that some vector x is a member of some set-- let me just say it's a member of rn, because that's what we deal with-- all that means is that this is just a particular representation of an n-tuple.
Now I have been all abstract and whatnot,so let me actually deal with some vectors and it might make everything a little bit more concrete.
So we can say that if you want to write some vector x, y, if you wanted to write with respect to this standard basis right here, it's going to be equal to the coordinates by the definition that we did earlier in this video of the basis vectors right there.
We could have written it-- and it's good to see all the different notations that you might encounter--you could write it a transformation of some vector x, where the vector looks like this, x1.
So another way we could say it is,if we write r times some vector x-- well I will just write it times this particular x-- where I write it as c1, c2, 0, c4, and 0 is equal to 0.
If I have some linear transformation that's a mapping from rn to rn, and if we're dealing with standard coordinates, that transformation--applied to some vector x in standard cooridenties-- will be equal to the matrix a times x.
Now, we have learned-- we have seen this several times already--that if I have some vector x in rn represented in b coordinates, or in coordinates with respect to b, I can multiply it by the change of basis matrix and then I will get just the standard coordinates for x.
What I want to show you is that when I do a change of basis-- we have seen this before-- in my standard coordinates or in coordinates with respect to the standardbasis, you give me some vector in Rn, I'm going to multiply it times A, and you're going to have the transformation of it.
So in the last video I said, look, in standard coordinates,if you have some vector x in your domain and you apply some transformation, then let's say that A is the transformation matrix with respect to the standard basis, then you're just going to have this mapping.
Now, we have seen many times before that if I have just any member of Rn-- So let's say that I have some vector x that is a member of Rn, then x can be represented as a sum of a member of V, as some vector V that is in our subspace,and some vector w, that is in the orthogonal complement of our subspace.