Up until now, our method for finding the coordinates of a vector in some new basis has been to set up a system of equations and solve for the coefficient variables. In this section, we will describe a different way, using matrices.
In fact, the first Theorem in this section is essentially a special case of Section 4.A, when applied to the identity transformation. One of the uses of the following matrix is to use Corollary 4.9 to convert the basis in the domain or codomain to something else.
For any vector space , the identity linear transformation is the function defined by . If and are bases for , then the change of basis matrix from to is:
The following theorem justifies this name.
Let and be two bases of the vector space over a field . Let . Then
The columns of are the vectors ,
For any we have ,
.
So when the target basis is the standard basis of , then columns of are simply the vectors in written in the standard coordinates.
Let be the standard basis of , and . Find the change of basis matrix , and hence find .
Solution: By Theorem 4.49, the change of basis matrix from to has columns equal to the basis vectors in written in the standard basis. So
If we set , then our goal is to find . According to Theorem 4.49, we have . We compute using methods of MATH105, and then we have:
So the coordinate matrix is in the basis .
Let be a basis of , and the standard basis of .
Find the change of basis matrix from to .
Find the inverse of , using the formula for the inverse of a matrix.
Compute by finding and .
[End of Exercise]
Let and be two bases of a vector space and assume is a linear transformation. Then the matrices associated to are related as follows:
, where
This follows directly from Corollary 4.9. ∎