Examples of using Linear transformations 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
They will be linear transformations.
Linear transformations and this condition.
I have two linear transformations.
In the next video I'm going to talk about linear transformations.
All linear transformations can be a matrix vector product.
Let's take three linear transformations.
That's one of the conditions, or one thing that we know is true for all linear transformations.
By definition, linear transformations have to satisfy these properties.
That's just from our definition of linear transformations.
Linear transformations, the sum of the transformations of two vectors is equal to the transformation of the sum of their of vectors.
Triangle area computation and linear transformations.
Now, from the definition of linear transformations, we know that this is the same thing, that the transformation of the sum is equal to the sum of the transformation. .
These are both conditions for linear transformations.
And we know that all linear transformations can be expressed as a multiplication of a matrix, but this one is equal to the matrix 1, 3, 2, 6 times whatever vector you give me in my domain.
We met both of our conditions for linear transformations.
And we asked ourselves, given these two linear transformations, could we construct a linear transformation that goes all the way from x to z?
In the last video we started off with two linear transformations.
Now, let's apply what we already know about linear transformations to what we have just learned about this identity matrix.
They're actually for the composition of two transformations where each of A and B are the transformation matrices for each of the individual linear transformations.
Is the composition of two linear transformations even a.
And the second thing we know is true for all linear transformations is, if we take the transformation of some scaled version of a vector in our domain, it is equal to the scaling factor times the transformation of the vector itself.
I could rewrite this, so everything I have done so far, so the transformation of x is equal to that, which just using our properties of linear transformations, all linear transformations, this has to be true for them.
And I did that because it has this neat property now because now the sum of two linear transformations operating on x is equivalent to, when you think of it is a matrix vector product, as the sum of their two matrices.
Linear transformation.
And any linear transformation you could actually represent as a matrix vector product.
This is any linear transformation.
We have this mapping, S, or this linear transformation, from X to Y.
Linear transformation S, applied to our two vectors, x plus y.
Linear transformation, we know that this can be rewritten as.
Linear transformation.