Transformations
A description of vector transformations and how they're preformed
Last updated
A description of vector transformations and how they're preformed
Last updated
We can transform a vector to change it into another vector. In general, this vector can be in the same or in a different vector space - for example, a vector along one plane could transform into a vector along another plane (Das, R ).
Transformations are labeled with a letter wearing a little hat - like this: . To apply the transformation, we multiply the vector by the transformation.
So, the expression...
...describes , which is a result of transformed by (multiplied by the matrix represented by) .
In general, we can use a matrix to define the actions preformed which result in a given transformation. We multiply a vector by the transformation to apply these operations in the proper order.
If you preform the multiplication here you'll see that this transformation didn't do anything - we call this the identity transformation because it gives us the identity of the matrix we transform it by. This special matrix will come in handy later.
This transformation rotated by .
In general, any matrix which can be "applied" or multiplied to another matrix can be a transformation.
In the case of a column vector, we're affecting some kind of change on it, taking one thing and "making" it into another. The old vector and the new vector share a particular relationship, which is described by the transformation matrix.
A linear transformation is a transformation that affects a vector within the context of vector spaces.
For example, we take a vector along one plane and transform it to a vector along another plane. Or perhaps we take a vector and rotate it within the same plane. We're talking about transformations within the context of linear relationships (Nykam, D ).
Operators are special linear transformations that transform a vector within it's vector space.
In this case we can't change a vector in one plane into a vector in another plane, but we can rotate a vector along the same plane. This means all operators are linear transformations, but not vice versa.