Solving Linear Transformations w/ Bases of Vector Spaces

In summary, the question asks to show that the set $\{f_1,f_2,f_3\}$ is a basis for the vector space $V$, given that $\{e_1,e_2,e_3\}$ is a basis and $T:V\rightarrow V$ is a linear transformation. This can be done by showing that the set is linearly independent and spans $V$. Furthermore, the matrix of $T$ with respect to the basis $\{e_1,e_2,e_3\}$ is given, and the task is to find the matrix with respect to the basis $\{f_1,f_2,f_3\}$. This can be done using the change-of-b
  • #1
Chris L T521
Gold Member
MHB
915
0
Here is the question:

george said:
Let $\{e_1, e_2, e_3\}$ be a basis for the vector space $V$ and $T: V \rightarrow V$ a linear transformation.

(a)
Show that if $f_1=e_1+e_2+e_3$, $f_2=e_1+e_2$, $f_3=e_1$ then $\{f_1,f_2,f_3\}$ is also a basis for $V$

(b)
Find the matrix $B$ of the $T$ with respect to the basis $\{e_1,e_2,e_3\}$ given that its matrix with respect to $\{f_1,f_2,f_3\}$ is
\[A = \begin{pmatrix}0 & 0 & 1\\ 0 & 1 & 1 \\ 1 & 1 & 1\end{pmatrix}\]

Here is a link to the question:

Let {e1, e2, e3} be a basis for the vector space V and T: V -> V a linear transformation.? - Yahoo! Answers

I have posted a link there to this topic so the OP can find my response.
 
Mathematics news on Phys.org
  • #2
Hello george,

Since $\{e_1,e_2,e_3\}$ forms a basis for $V$, we see that they're linearly independent, i.e. for scalars $c_1,c_2,c_3\in\mathbb{R}$ (or any field of interest) $c_1e_1+c_2e_2+c_3e_3 = 0 \iff c_1=c_2=c_3=0$. Now, let $d_1,d_2,d_3\in\mathbb{R}$. We now consider the equation $d_1f_1+d_2f_2+d_3f_3 = 0$. Since $f_1=e_1+e_2+e_3$, $f_2=e_1+e_2$ and $f_3=e_1$, we see that
\[\begin{aligned} d_1f_1+d_2f_2+d_3f_3 = 0 &\implies d_1(e_1+e_2+e_3) + d_2(e_1+e_2) + d_3(e_3) = 0 \\ & \implies (d_1+d_2+d_3)e_1 + (d_1+d_2)e_2 + d_1e_3 = 0\end{aligned}\]
Since $\{e_1,e_2,e_3\}$ was a basis, we must now have that
\[\left\{\begin{aligned} d_1 + d_2 + d_3 &= 0\\ d_1 + d_2 &= 0 \\ d_1 &= 0\end{aligned}\right.\]
which clearly has the solution $d_1=d_2=d_3=0$. Therefore, $d_1f_1 + d_2f_2 + d_3f_3 = 0 \iff d_1=d_2=d_3=0$ and hence $\{f_1,f_2,f_3\}$ is a linearly independent set in $V$. Furthermore, $\mathrm{Span}\{f_1,f_2,f_3\} = \mathrm{Span}\{e_1,e_2,e_3\} = V$; hence, $\{f_1,f_2,f_3\}$ is also a basis for $V$.Next, we're told that in terms of the basis $\{f_1,f_2,f_3\}$, the linear transformation $T:V\rightarrow V$ is represented by the matrix
\[A = \begin{pmatrix}T(f_1) & T(f_2) & T(f_3)\end{pmatrix} = \begin{pmatrix}0 & 0 & 1\\ 0 & 1 & 1 \\ 1 & 1 & 1\end{pmatrix}\]
Since $f_1 = e_1 + e_2 + e_3$, $f_2 = e_1 + e_2$, and $f_3 = e_1$, we see that
\[T(f_1) = T(e_1) + T(e_2) + T(e_3),\quad T(f_2) = T(e_1) + T(e_2),\quad\text{and}\quad T(f_3) = T(e_1).\]
Comparing the columns of these two matrices, we have the system of equations
\[\left\{\begin{aligned}T(e_1) + T(e_2) + T(e_3) &= { \begin{pmatrix}0\\ 0 \\ 1\end{pmatrix}} \\ T(e_1) + T(e_2) &= {\begin{pmatrix} 0 \\ 1 \\ 1\end{pmatrix}} \\ T(e_1) &= {\begin{pmatrix}1 \\ 1 \\ 1\end{pmatrix} }\end{aligned}\right.\]
Solving this system yields that
\[T(e_1) = \begin{pmatrix}1\\ 1\\ 1\end{pmatrix},\quad T(e_2) = \begin{pmatrix}-1\\ 0 \\ 0\end{pmatrix},\quad\text{and}\quad T(e_3) = \begin{pmatrix}0 \\ -1 \\ 0\end{pmatrix}\]
Therefore, in terms of the basis $\{e_1,e_2,e_3\}$, the linear transformation $T:V\rightarrow V$ is represented by the matrix
\[B = \begin{pmatrix} T(e_1) & T(e_2) & T(e_3)\end{pmatrix} = \begin{pmatrix}1 & -1 & 0\\ 1 & 0 & -1\\ 1 & 0 & 0\end{pmatrix}\]I hope this makes sense!
 
  • #3
Chris L T521 said:
Here is the question:
Here is a link to the question:

Let {e1, e2, e3} be a basis for the vector space V and T: V -> V a linear transformation.? - Yahoo! Answers

I have posted a link there to this topic so the OP can find my response.
An alternativ way for a) is to check that that \(\displaystyle det \neq 0\) but the way Chris L T521 is probably the best!
2rh9oat.jpg

Basicly what I did Was put \(\displaystyle f_1,f_2,f_3\) as a columne to a matrice and Then calculate the determinant! (You can se in picture which is \(\displaystyle f_1,f_2,f_3\)

Regards,
\(\displaystyle |\pi\rangle\)
 
  • #4
Alternative 3:

Because the set $\{f_1,f_2,f_3\}$ has 3 elements it suffices to show that this set spans $V$ (since $V$ has dimension 3 because of the size of the given basis).

We have:

$e_1 = f_3$
$e_2 = f_2 - f_3$
$e_3 = f_1 - f_2$

so $c_1e_1 + c_2e_2 + c_3e_3 = c_1(f_3) + c_2(f_2 - f_3) + c_3(f_1 - f_2)$

$= c_3f_1 + (c_2 - c_3)f_2 + (c_1 - c_2)f_3 \in \text{span}(\{f_1,f_2,f_3\})$.

***********
Before tackling the second question, it bears looking into what the change-of-basis matrix $P$ is:

$P = \begin{bmatrix}0&0&1\\0&1&-1\\1&-1&0 \end{bmatrix}$

If we call our bases B (for the $e$'s) and C (for the $f$'s), then:

$P([\mathbf{v}]_B) = [\mathbf{v}]_C$

The problem gives us $P^{-1}$ straight off the bat, it is:

$P^{-1} = \begin{bmatrix}1&1&1\\1&1&0\\1&0&0 \end{bmatrix}$

So the matrix we desire is:

$A' = P^{-1}AP$, which sends:

$[\mathbf{v}]_B \to [\mathbf{v}]_C \to [T(\mathbf{v})]_C \to [T(\mathbf{v})]_B$

Computing, we have:

$A' = P^{-1}AP = \begin{bmatrix}1&1&1\\1&1&0\\1&0&0 \end{bmatrix} \begin{bmatrix}0&0&1\\0&1&1\\1&1&1 \end{bmatrix} \begin{bmatrix}0&0&1\\0&1&-1\\1&-1&0 \end{bmatrix}$

$ = \begin{bmatrix}1&2&3\\0&1&2\\0&0&1 \end{bmatrix} \begin{bmatrix}0&0&1\\0&1&-1\\1&-1&0 \end{bmatrix}$

$ = \begin{bmatrix}3&-1&-1\\2&-1&-1\\1&-1&0 \end{bmatrix}$

Huh. I get a different matrix. One of us must be wrong, who is it?

Chris L T521 writes:

$T(f_3) = T(e_1) = \begin{pmatrix}1\\1\\1 \end{pmatrix}$

This is misleading...coordinates don't tell us which vector we have UNTIL we choose a basis. What we actually have is:

$T(e_1) = T(f_3) = f_1 + f_2 + f_3 = (e_1 + e_2 + e_3) + (e_1 + e_2) + e_3 = 3e_1 + 2e_2 + e_3$.

We should expect that in the B-basis, $A'$ should map (1,0,0) to (3,2,1). I think I am correct.

EDIT:

Chris L T521, the mistake you made is that your images for $T(e_j)$ are still in the C-basis, you need to convert these back to the B-basis.
 
Last edited:
  • #5
Deveno said:
Alternative 3:

Because the set $\{f_1,f_2,f_3\}$ has 3 elements it suffices to show that this set spans $V$ (since $V$ has dimension 3 because of the size of the given basis).

We have:

$e_1 = f_3$
$e_2 = f_2 - f_3$
$e_3 = f_1 - f_2$

so $c_1e_1 + c_2e_2 + c_3e_3 = c_1(f_3) + c_2(f_2 - f_3) + c_3(f_1 - f_2)$

$= c_3f_1 + (c_2 - c_3)f_2 + (c_1 - c_2)f_3 \in \text{span}(\{f_1,f_2,f_3\})$.

***********
Before tackling the second question, it bears looking into what the change-of-basis matrix $P$ is:

$P = \begin{bmatrix}0&0&1\\0&1&-1\\1&-1&0 \end{bmatrix}$

If we call our bases B (for the $e$'s) and C (for the $f$'s), then:

$P([\mathbf{v}]_B) = [\mathbf{v}]_C$

The problem gives us $P^{-1}$ straight off the bat, it is:

$P^{-1} = \begin{bmatrix}1&1&1\\1&1&0\\1&0&0 \end{bmatrix}$

So the matrix we desire is:

$A' = P^{-1}AP$, which sends:

$[\mathbf{v}]_B \to [\mathbf{v}]_C \to [T(\mathbf{v})]_C \to [T(\mathbf{v})]_B$

Computing, we have:

$A' = P^{-1}AP = \begin{bmatrix}1&1&1\\1&1&0\\1&0&0 \end{bmatrix} \begin{bmatrix}0&0&1\\0&1&1\\1&1&1 \end{bmatrix} \begin{bmatrix}0&0&1\\0&1&-1\\1&-1&0 \end{bmatrix}$

$ = \begin{bmatrix}1&2&3\\0&1&2\\0&0&1 \end{bmatrix} \begin{bmatrix}0&0&1\\0&1&-1\\1&-1&0 \end{bmatrix}$

$ = \begin{bmatrix}3&-1&-1\\2&-1&-1\\1&-1&0 \end{bmatrix}$

Huh. I get a different matrix. One of us must be wrong, who is it?

Chris L T521 writes:

$T(f_3) = T(e_1) = \begin{pmatrix}1\\1\\1 \end{pmatrix}$

This is misleading...coordinates don't tell us which vector we have UNTIL we choose a basis. What we actually have is:

$T(e_1) = T(f_3) = f_1 + f_2 + f_3 = (e_1 + e_2 + e_3) + (e_1 + e_2) + e_3 = 3e_1 + 2e_2 + e_3$.

We should expect that in the B-basis, $A'$ should map (1,0,0) to (3,2,1). I think I am correct.

EDIT:

Chris L T521, the mistake you made is that your images for $T(e_j)$ are still in the C-basis, you need to convert these back to the B-basis.

Ah, after posting my answer, I had a slight feeling something was off with the matrix I came up with. Thanks a bunch for clarifying that!
 

FAQ: Solving Linear Transformations w/ Bases of Vector Spaces

What is a linear transformation?

A linear transformation is a mathematical operation that maps one vector space to another in a way that preserves the structure of the space. In other words, the output of a linear transformation can be obtained by multiplying the input vector by a matrix.

What is a basis of a vector space?

A basis of a vector space is a set of linearly independent vectors that can be used to represent any vector in that space. This means that every vector in the space can be written as a unique combination of the basis vectors.

Why is it important to solve linear transformations with bases of vector spaces?

Solving linear transformations with bases of vector spaces allows us to easily represent and manipulate vectors in a mathematical framework. It also helps us understand the properties of a vector space and how transformations affect vectors in that space.

How do you solve a linear transformation using bases of vector spaces?

To solve a linear transformation using bases of vector spaces, you first need to find a basis for the input and output vector spaces. Then, you can represent the transformation using a matrix and perform matrix multiplication to obtain the output vector.

What are some real-world applications of solving linear transformations with bases of vector spaces?

Solving linear transformations with bases of vector spaces has many real-world applications, such as in computer graphics, data compression, and machine learning. It is also used in physics and engineering to model and analyze systems.

Similar threads

Replies
2
Views
1K
Replies
2
Views
1K
Replies
1
Views
971
Replies
14
Views
2K
Replies
4
Views
2K
Replies
4
Views
248
Back
Top