Linear algebra: Transformations

In summary, the conversation discusses finding the matrix representation of a linear transformation with respect to different bases. The attempt at a solution involves finding the matrix representation with respect to the standard basis and then with respect to a given basis, and multiplying them together. However, this approach does not work due to the dimensions of the matrices. Another approach suggested is to first find the transformation in the standard basis and then use transformation matrices to convert to the given basis. This involves finding the transformation matrix for each basis and performing matrix multiplication.
  • #1
Niles
1,866
0

Homework Statement


A linear transformation L : R2 -> R3 is defined by:

[tex]L({\bf{x}}) = \left( {x_2 ,x_1 + x_2 ,x_1 - x_2 } \right)^T[/tex]

I wish to find the matrix representation of L with respect to the orderes bases [u1, u2] and [b1, b2, b3], where

u1 = (1,2)
u2 = (3,1)

andb1 = (1,0,0)
b2 = (1,1,0)
b3 = (1,1,1).

The Attempt at a Solution


Ok, I what I want to do is to find the matrix representation of L with respect to U and the standard basis E (I call this matrix A), and then find the matrix representation of L with respect to E and B (I call this matrix X). Then I will multiply these two matrices:

[tex]\[
A = \left( {\begin{array}{*{20}c}
2 \hfill & 1 \hfill \\
3 \hfill & 4 \hfill \\
{ - 1} \hfill & 2 \hfill \\
\end{array}} \right)
\]
[/tex]

and

[tex]\[
X = \left( {\begin{array}{*{20}c}
{ - 1} \hfill & 0 \hfill \\
0 \hfill & 2 \hfill \\
1 \hfill & { - 1} \hfill \\
\end{array}} \right)
\]
[/tex].

I believe that the matrix I am being asked for is X*A. But this won't work because of the dimensions. What am I missing here?Niles.
 
Physics news on Phys.org
  • #2
If we define [itex]_u(x)[/itex] to be the coordinates of the vector x in the basis [itex]u = \{u_{1},u_{2}\}[/itex] (with x in [itex]\matbb{R}^{2}[/itex]) and [itex]_{b}(L(x))[/itex] the coordinates of the vector L(x) in the basis [itex]b = \{b_{1},b_{2},b_{3}\}[/itex], then we have:

[tex]_b(L(x))=_{b}(L)_{u}\thinspace_{u}(x)[/tex]

where [itex]_{b}(L)_{u}[/itex] is the matrix in which the j-th column is given by [itex]_b(L({u}_{j}))[/itex] (the coordinates of [itex]L({u}_{j})[/itex] in the basis [itex]b = \{b_{1},b_{2},b_{3}\}[/itex])

The matrix representation of L is the matrix [itex]_{b}(L)_{u}[/itex]

The first column would be calculated this way:

[tex]L({u}_{1}) = (2,3,-1)^{T} = -b_{1} + 4b_{2} - b_{3}[/tex]

(As you can check). And

[tex]_{b}(L({u}_{1})) = (-1,4,-1)^{T}[/tex]

gives you the first column.
 
  • #3
The way I was thinking of doing this is first finding L in the basis of (1,0), (0,1)-> (1,0,0),(0,1,0),(0,0,1) since this is easily done and then putting an transform matrix on each side of it. To the right of L you would want a matrix that goes from [tex]{u_1,u_2}[/tex] to (1,0),(0,1) and on the left side a matrix that transforms from (1,0,0),(0,1,0),(0,0,1) to [tex]{b_1,b_2,b_3}[/tex]. The L matrix should be 3 x 2. The right side transform matrix should be 2 x 2 and the left side transform matrix should be 3 x 3. Just my 2 cents as to how I think of approaching a problem like this.
 
  • #4
You can approach the problem this way:

Let [itex]x_1,x_2[/itex] be the coefficients of basis vectors u1, u2 and [itex]c_1,c_2,c_3[/itex] be the coefficients of the basis vectors b1,b2,b3. So by your notation, we have [tex]A(x_1\vec{u_1} + x_2\vec{u_2}) = c_1\vec{b_1} + c_2\vec{b_2} + c_3\vec{b_3}[/tex].

So the matrix multiplication on the left can be seen as

[tex]\left( \begin{array}{ccc} A\vec{u_1}&A\vec{u_2} \end{array} \right) \left(\begin{array}{c}x_1\\x_2 \end{array}\left) = (\vec{b_1} \ \vec{b_2} \ \vec{b_3}) \left( \begin{array}{c}c_1\\c_2\\c_3 \end{array} \right)[/tex]

where Au1, Au2 and bn are column vectors in the matrix. Now, you should be able to find c1,c2,c3.
 

Related to Linear algebra: Transformations

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another while preserving the structure of the original vector space. In other words, it is a function that takes in vectors as inputs and outputs new vectors that are related in a specific way.

2. How do you represent a linear transformation?

A linear transformation can be represented by a matrix. The columns of the matrix represent the images of the basis vectors of the original vector space. The transformation can then be applied to any vector by multiplying it with this matrix.

3. What is the difference between a linear transformation and a linear combination?

A linear transformation is a function, while a linear combination is a mathematical expression. A linear combination involves multiplying vectors by constants and adding them together, while a linear transformation involves applying a function to a vector.

4. Can a linear transformation change the dimension of a vector space?

Yes, a linear transformation can change the dimension of a vector space. This can happen, for example, when the transformation collapses multiple dimensions of the original vector space into a single dimension in the output vector space.

5. How is the composition of linear transformations calculated?

The composition of two linear transformations is calculated by multiplying their respective matrices. The resulting matrix will represent the composition of the two transformations.

Similar threads

  • Calculus and Beyond Homework Help
Replies
3
Views
1K
  • Calculus and Beyond Homework Help
Replies
8
Views
1K
  • Calculus and Beyond Homework Help
Replies
2
Views
563
  • Calculus and Beyond Homework Help
Replies
12
Views
4K
  • Calculus and Beyond Homework Help
Replies
7
Views
1K
  • Calculus and Beyond Homework Help
Replies
8
Views
804
  • Calculus and Beyond Homework Help
Replies
22
Views
2K
Replies
2
Views
2K
  • Calculus and Beyond Homework Help
Replies
0
Views
215
  • Calculus and Beyond Homework Help
Replies
2
Views
896
Back
Top