Linear Transformation with Respect to Given Bases

In summary, for the linear transformation T: R3 -> M(2,2), the matrix with respect to bases B and C is [ 0 0 0 1; 0 0 0 -1; 1 -1 0 0 ]. Part (b) involves finding the column space of this matrix and part (c) involves finding the solution space. The method used to find this matrix is to take each vector from B, apply the transformation, and write it in terms of the basis C. The question is whether this matrix is correct or if it should be transposed.
  • #1
forty
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0
Let T: R3 -> M(2,2) be the linear transformation given by

T(x,y,z) = [ z ...-z ]
.....[ 0 ... x-y]Fix bases B = {(1,0,0),(0,1,0),(0,0,1)} and C = { [1 0] , [0 1] , [0 0] , [0 0] }
............[0 0]...[0 0]...[1 0]...[0 1]for R3 and M(2,2) respectivelya) Find the matrix [T]c,b of T with respect to the bases B and C.
b) Use the matrix from part (a) to find the basis for Im(T)
c) Use the matrix from part (a) to find the basis for Ker(T)

For parts b and c I'm pretty sure that's just finding the column space (part b) and solution space (part c) of the matrix.

As for a its more so to do with my own confusion when it comes to bases.

I worked out the matrix to be [ 0 0 0 1 ]
...(3 by 4 matrix)...[ 0 0 0 -1]
.......[ 1 -1 0 0]

The way i got this was by taking each vector from B applying the transformation then writing it in terms of the basis C and then writing the coefficients of each matrix in the rows of the above matrix. I hope that even makes sense >_>.

Any help greatly appreciated :)

P.S. sorry for the garbagety matrices :SEDIT: Maybe its the transpose of that matrix... I am lost >.<
 
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  • #2
Yes, the way you found the matrix certainly makes sense and, in fact, is the best way to do it. It is also true that "For parts b and c I'm pretty sure that's just finding the column space (part b) and solution space (part c) of the matrix."

Now, since you have done part (a) and know how to do parts (b) and (c), what is your question?
 
  • #3
So the first matrix i got is correct?

[ 0 0 0 1 ]
[ 0 0 0 -1]
[ 1 -1 0 0]or is is the transpose of it?
 

Related to Linear Transformation with Respect to Given Bases

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another, preserving the basic structure of the vector space. This means that the transformation preserves linear combinations and the origin point.

2. What is a basis in linear transformation?

A basis is a set of linearly independent vectors that can be used to represent any vector in a vector space. In linear transformation, a basis is used to define the transformation and determine its effects on vectors.

3. How do you represent a linear transformation?

A linear transformation can be represented using a matrix. The columns of the matrix correspond to the images of the basis vectors under the transformation.

4. What is the relationship between linear transformations and matrices?

Linear transformations and matrices are closely related. The matrix representation of a linear transformation can help us visualize and understand its effects on vectors. Additionally, matrix multiplication is used to perform linear transformations on vectors.

5. What is the difference between a linear transformation and a non-linear transformation?

A linear transformation preserves the structure of a vector space, while a non-linear transformation does not. This means that a linear transformation preserves linear combinations and the origin point, while a non-linear transformation does not necessarily do so.

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