- #1
GwtBc said:Ok I can see the logic that led you through this attempt but it's not quite correct. First off you have a 3x3 matrix for a transformation that goes from a 3-D space to a 2-D one. This is already troublesome. You want your number of columns to be equal to ##\dim{U}## and the number of rows to be equal to the dimension of your target space i.e. ##\dim{V}##. So in this case you want a 2x3 matrix.
As for the entries of the matrix, each column is directed by letting ##T## act on a basis vector from ##U##. For example, if we have the vector ##
\begin{pmatrix} 1\\ 0\\ 0
\end{pmatrix}## which represents a constant polynomial equal to ##1##, then ##T(
\begin{pmatrix} 1\\ 0\\ 0
\end{pmatrix})## gives us ##
\begin{pmatrix}
1\\
0
\end{pmatrix}## as represented by the basis ##F## in the space ##V##.
That's just how ##T## is defined. It's a transformation that takes a vector from a 3-D space to a 2-D space. In terms of the actual calculation, you let ##T## operate on a basis vectors of E (which is a basis for ##U##). So the first one is ##\begin{pmatrix} 1\\ 0\\0 \end{pmatrix}## which represents the polynomial ##f(t) = 1##. Then ##f(3) = 1## and ##f'(3)=0##, which if represented by the basis vectors of ##F## (which is a basis for ##V##) is ##\begin{pmatrix} 1\\ 0 \end{pmatrix}##Robb said:Ok, I guess I'm unsure of
##T(
\begin{pmatrix} 1\\ 0\\ 0
\end{pmatrix})## gives us ##
\begin{pmatrix}
1\\
0
How does this go from a 3x1 to a 2x1 vector. I'm not seeing the math behind it.
A matrix representation relative to bases is a way of representing linear transformations between vector spaces using matrices. It allows for easy computation and understanding of these transformations.
Matrix representation relative to bases is important because it gives us a way to visualize and manipulate linear transformations between vector spaces. It also allows us to perform calculations and solve problems related to these transformations.
The matrix representation relative to bases can be determined by choosing a basis for the domain and range vector spaces, and then representing the linear transformation as a matrix with respect to these bases. This matrix will have the same dimensions as the number of elements in the bases.
Matrix representation relative to bases is closely related to change of basis. In fact, the matrix representation of a linear transformation can change depending on the basis chosen for the vector spaces. This is why understanding change of basis is important in understanding matrix representation relative to bases.
No, matrix representation relative to bases is only applicable for linear transformations between vector spaces. Non-linear transformations cannot be represented using matrices.