Linear Transformation $T:\R^2 \to \R^2$ Given in Figure

Linear Transformation problems and solutions

Problem 610

Let $T:\R^2\to \R^2$ be a linear transformation such that it maps the vectors $\mathbf{v}_1, \mathbf{v}_2$ as indicated in the figure below.

linear transformation from R^2 to R^2

Find the matrix representation $A$ of the linear transformation $T$.

 
LoadingAdd to solve later

Sponsored Links


Solution 1.

From the figure, we see that
\[\mathbf{v}_1=\begin{bmatrix}
-3\\ 1
\end{bmatrix} \text{ and } \mathbf{v}_2=\begin{bmatrix}
5\\ 2
\end{bmatrix},\] and
\[T(\mathbf{v}_1)=\begin{bmatrix}
2\\ 2
\end{bmatrix} \text{ and } T(\mathbf{v}_2)=\begin{bmatrix}
1\\ 3
\end{bmatrix}.\]


Let $A$ be the matrix representation of the linear transformation $T$. By definition, we have $T(\mathbf{x})=A\mathbf{x}$ for any $\mathbf{x}\in \R^2$.

We determine $A$ as follows.
We have
\begin{align*}
\begin{bmatrix}
2& 1 \\
2& 3
\end{bmatrix}
&=[T(\mathbf{v}_1), T(\mathbf{v}_2)]\\
&=[A\mathbf{v}_1, A\mathbf{v}_2]\\
&=A[\mathbf{v}_1, \mathbf{v}_2]\\
&=A\begin{bmatrix}
-3& 5 \\
1& 2
\end{bmatrix}.
\end{align*}


Note that the determinant of the leftmost matrix is $-11$, hence it is invertible and the inverse is given by
\[\begin{bmatrix}
-3& 5 \\
1& 2
\end{bmatrix}^{-1}=\frac{1}{11}\begin{bmatrix}
-2& 5 \\
1& 3
\end{bmatrix}.
\] Hence
\begin{align*}
A&= \begin{bmatrix}
2& 1 \\
2& 3
\end{bmatrix} \begin{bmatrix}
-3& 5 \\
1& 2
\end{bmatrix}^{-1}\\[6pt] &=\frac{1}{11}\begin{bmatrix}
2& 1 \\
2& 3
\end{bmatrix}\begin{bmatrix}
-2& 5 \\
1& 3
\end{bmatrix}. \\[6pt] &=\frac{1}{11}\begin{bmatrix}
-3& 13 \\
-1& 19
\end{bmatrix}.
\end{align*}

Therefore, the matrix representation of $T$ is
\[A=\frac{1}{11}\begin{bmatrix}
-3& 13 \\
-1& 19
\end{bmatrix}.\]

Solution 2.

Let $\{\mathbf{e}_1, \mathbf{e}_2\}$ be the standard basis for $\R^2$.
Then the matrix representation $A$ of the linear transformation $T$ is given by
\[A=[T(\mathbf{e}_1), T(\mathbf{e}_2)].\] From the figure, we see that
\[\mathbf{v}_1=\begin{bmatrix}
-3\\ 1
\end{bmatrix} \text{ and } \mathbf{v}_2=\begin{bmatrix}
5\\ 2
\end{bmatrix},\] and
\[T(\mathbf{v}_1)=\begin{bmatrix}
2\\ 2
\end{bmatrix} \text{ and } T(\mathbf{v}_2)=\begin{bmatrix}
1\\ 3
\end{bmatrix}.\]


The values of $T(\mathbf{e}_1)$ and $T(\mathbf{e}_2)$ are not indicated in the figure but we can determine these values as follows.
Note that $\{\mathbf{v}_1, \mathbf{v}_2\}$ is a basis for $\R^2$ (as they are linearly independent from the figure).

Let us express $\mathbf{e}_1$ as a linear combination of $\mathbf{v}-1$ and $\mathbf{v}_2$.
Let
\[\mathbf{e}_1=c_1\mathbf{v}_1+c_2\mathbf{v}_2,\] where $c_1, c_2$ are scalars to be determined.

This is equivalent to
\[\begin{bmatrix}
1
\\ 0
\end{bmatrix}
=[\mathbf{v}_1, \mathbf{v}_2]\begin{bmatrix}
c_1\\ c_2
\end{bmatrix}
=\begin{bmatrix}
-3
& 5 \\
1& 2
\end{bmatrix}
\begin{bmatrix}
c_1\\ c_2
\end{bmatrix}.\]

As we have
\[\begin{bmatrix}
-3& 5 \\
1& 2
\end{bmatrix}^{-1}=\frac{1}{11}\begin{bmatrix}
-2& 5 \\
1& 3
\end{bmatrix},
\] it follows that
\begin{align*}
\begin{bmatrix}
c_1\\ c_2
\end{bmatrix}
=\begin{bmatrix}
-3& 5 \\
1& 2
\end{bmatrix}^{-1}\begin{bmatrix}
1\\ 0
\end{bmatrix}=
\frac{1}{11}\begin{bmatrix}
-2& 5 \\
1& 3
\end{bmatrix}
\begin{bmatrix}
1\\ 0
\end{bmatrix}
= \frac{1}{11}\begin{bmatrix}
-2
\\ 1
\end{bmatrix}.
\end{align*}
Thus, we obtain the linear combination
\[\mathbf{e}_1=-\frac{2}{11}\mathbf{v}_1+\frac{1}{11}\mathbf{v}_2,\]


By the linearity of $T$, we have
\begin{align*}
T(\mathbf{e}_1)&=-\frac{2}{11}T(\mathbf{v}_1)+\frac{1}{11}T(\mathbf{v}_2)\\
&=-\frac{2}{11}\begin{bmatrix}
2
\\ 2
\end{bmatrix}
+\frac{1}{11}\begin{bmatrix}
1\\ 3
\end{bmatrix}
\\
&=\frac{1}{11}\begin{bmatrix}
-3\\ -1
\end{bmatrix}.
\end{align*}


Similarly, let
\[\mathbf{e}_2=d_1\mathbf{v}_1+d_2\mathbf{v}_2,\] where $d_1, d_2$ are scalars to be determined.
Then we have
\[\begin{bmatrix}
0\\ 1
\end{bmatrix}
=\begin{bmatrix}
-3 & 5 \\
1& 2
\end{bmatrix}
\begin{bmatrix}
d_1\\ d_2
\end{bmatrix}.\] It follows that
\begin{align*}
\begin{bmatrix}
d_1\\ d_2
\end{bmatrix}
=\begin{bmatrix}
-3& 5 \\
1& 2
\end{bmatrix}^{-1}\begin{bmatrix}
0\\ 1
\end{bmatrix}=
\frac{1}{11}\begin{bmatrix}
-2& 5 \\
1& 3
\end{bmatrix}
\begin{bmatrix}
0\\ 1
\end{bmatrix}
= \frac{1}{11}\begin{bmatrix}
5
\\ 3
\end{bmatrix}.
\end{align*}
Thus, we have the linear combination
\[\mathbf{e}_2=\frac{5}{11}\mathbf{v}_1+\frac{3}{11}\mathbf{v}_2,\] and by linearity of $T$ we obtain
\begin{align*}
T(\mathbf{e}_2)&=\frac{5}{11}T(\mathbf{v}_1)+\frac{3}{11}T(\mathbf{v}_2)\\
&=\frac{5}{11}T(\mathbf{v}_1)+\frac{3}{11}T(\mathbf{v}_2)\\
&=\frac{5}{11}\begin{bmatrix}
2
\\ 2
\end{bmatrix}
+\frac{3}{11}\begin{bmatrix}
1\\ 3
\end{bmatrix}
\\
&=\frac{1}{11}\begin{bmatrix}
13\\ 19
\end{bmatrix}.
\end{align*}


In conclusion, the matrix representation for $T$ is
\[A=[T(\mathbf{e}_1), T(\mathbf{e}_2)]=\frac{1}{11}\begin{bmatrix}
-3& 13 \\
-1& 19
\end{bmatrix}.\]


LoadingAdd to solve later

Sponsored Links

More from my site

You may also like...

Please Login to Comment.

This site uses Akismet to reduce spam. Learn how your comment data is processed.

More in Linear Algebra
Problems and Solutions of Eigenvalue, Eigenvector in Linear Algebra
Eigenvalues of $2\times 2$ Symmetric Matrices are Real by Considering Characteristic Polynomials

Let $A$ be a $2\times 2$ real symmetric matrix. Prove that all the eigenvalues of $A$ are real numbers by...

Close