Difference between revisions of "031 Review Part 3, Problem 5"

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{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Step 1:    
 
!Step 1:    
 +
|-
 +
|To diagonalize this matrix, we need to find the eigenvalues and a basis for each eigenspace.
 +
|-
 +
|First, we find the eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; by solving &nbsp;<math style="vertical-align: -5px">\text{det }(A-\lambda I)=0.</math>
 +
|-
 +
|&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{array}{rcl}
 +
\displaystyle{\text{det }(A-\lambda I)} & = & \displaystyle{\text{det }\bigg(\begin{bmatrix}
 +
          1 & -6  \\
 +
          2 & -6 
 +
        \end{bmatrix}-\begin{bmatrix}
 +
          \lambda & 0  \\
 +
          0 & \lambda   
 +
        \end{bmatrix}\bigg)}\\
 +
&&\\
 +
& = & \displaystyle{\text{det }\bigg(\begin{bmatrix}
 +
            1-\lambda & -6  \\
 +
          2 & -6-\lambda 
 +
        \end{bmatrix}\bigg)}\\
 +
&&\\
 +
& = & \displaystyle{(1-\lambda)(-6\lambda)+12}\\
 +
&&\\
 +
& = & \displaystyle{\lambda^2+5\lambda+6}\\
 +
&&\\
 +
& = & \displaystyle{(\lambda+2)(\lambda+3).}\\
 +
\end{array}</math>
 +
|-
 +
|Therefore, setting
 
|-
 
|-
 
|
 
|
 +
::<math>(\lambda+2)(\lambda+3)=0,</math>&nbsp;
 +
|-
 +
|we find that the eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; are &nbsp;<math style="vertical-align: 0px">-2</math>&nbsp; and &nbsp;<math style="vertical-align: 0px">3.</math>
 
|}
 
|}
  
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Step 2: &nbsp;
 
!Step 2: &nbsp;
 +
|-
 +
|Now, we find a basis for each eigenspace by solving &nbsp;<math style="vertical-align: -6px">(A-\lambda I)\vec{x}=\vec{0}</math>&nbsp; for each eigenvalue &nbsp;<math style="vertical-align: 0px">\lambda.</math>
 +
|-
 +
|For the eigenvalue &nbsp;<math style="vertical-align: -4px">\lambda=-2,</math>&nbsp; we have
 +
|-
 +
|
 +
&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{array}{rcl}
 +
\displaystyle{A+2I} & = & \displaystyle{\begin{bmatrix}
 +
            1 & -6  \\
 +
          2 & -6
 +
        \end{bmatrix}+\begin{bmatrix}
 +
          2 & 0  \\
 +
          0 & 2 
 +
        \end{bmatrix}}\\
 +
&&\\
 +
& = & \displaystyle{\begin{bmatrix}
 +
          3 & -6  \\
 +
          2 & -4
 +
        \end{bmatrix}}\\
 +
&&\\
 +
& \sim & \displaystyle{\begin{bmatrix}
 +
          1 & -2 \\
 +
          0 & 0 
 +
        \end{bmatrix}.}
 +
\end{array}</math>
 +
|-
 +
|We see that &nbsp;<math style="vertical-align: -3px">x_2</math>&nbsp; is a free variable. So, a basis for the eigenspace corresponding to &nbsp;<math style="vertical-align: 0px">-2</math>&nbsp; is 
 +
|-
 +
|
 +
::<math>\bigg\{\begin{bmatrix}
 +
          2  \\
 +
          1 \\ 
 +
        \end{bmatrix}\bigg\}.</math>
 +
 +
|}
 +
 +
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 +
!Step 3: &nbsp;
 +
|-
 +
|For the eigenvalue &nbsp;<math style="vertical-align: -4px">\lambda=-3,</math>&nbsp; we have
 +
|-
 +
|
 +
&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{array}{rcl}
 +
\displaystyle{A+3I} & = & \displaystyle{\begin{bmatrix}
 +
          1 & -6  \\
 +
          2 & -6 
 +
        \end{bmatrix}-\begin{bmatrix}
 +
          3 & 0 \\
 +
          0 & 3 
 +
        \end{bmatrix}}\\
 +
&&\\
 +
& = & \displaystyle{\begin{bmatrix}
 +
          4 & -6 \\
 +
          2 & -3
 +
        \end{bmatrix}}\\
 +
&&\\
 +
& \sim & \displaystyle{\begin{bmatrix}
 +
          1 & \frac{-3}{2} \\
 +
          0 & 0 
 +
        \end{bmatrix}.}
 +
\end{array}</math>
 +
|-
 +
|We see that &nbsp;<math style="vertical-align: -3px">x_2</math>&nbsp; is a free variable. So, a basis for the eigenspace corresponding to &nbsp;<math style="vertical-align: 0px">-3</math>&nbsp; is 
 +
|-
 +
|
 +
::<math>\bigg\{\begin{bmatrix}
 +
          \frac{3}{2}  \\
 +
          1 \\
 +
        \end{bmatrix}\bigg\}.</math>
 +
|}
 +
 +
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 +
!Step 4: &nbsp;
 +
|-
 +
|To diagonalize our matrix, we use the information from the steps above.
 +
|-
 +
|
 +
Using the Diagonalization Theorem, we have &nbsp;<math style="vertical-align: -1px">A=PDP^{-1}</math>&nbsp; where
 +
|-
 +
|
 +
::<math>D=\begin{bmatrix}
 +
          -2 & 0 \\
 +
          0 & -3 
 +
        \end{bmatrix},P=\begin{bmatrix}
 +
          2 & \frac{3}{2} \\
 +
          1 & 1 
 +
        \end{bmatrix}.</math>
 +
|}
 +
 +
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 +
!Step 5: &nbsp;
 +
|-
 +
|Notice that
 
|-
 
|-
 
|
 
|
 +
&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{array}{rcl}
 +
\displaystyle{A^k} & = & \displaystyle{(PDP^{-1})^k}\\
 +
&&\\
 +
& = & \displaystyle{PD^kP^{-1}}\\
 +
&&\\
 +
& = & \displaystyle{\begin{bmatrix}
 +
          2 & \frac{3}{2} \\
 +
          1 & 1 
 +
        \end{bmatrix}\bigg(\begin{bmatrix}
 +
          -2 & 0 \\
 +
          0 & -3 
 +
        \end{bmatrix}\bigg)^k (-2)\begin{bmatrix}
 +
          1 & -\frac{3}{2} \\
 +
          -1 & 2 
 +
        \end{bmatrix}}\\
 +
&&\\
 +
& = & \displaystyle{\begin{bmatrix}
 +
          2 & \frac{3}{2} \\
 +
          1 & 1 
 +
        \end{bmatrix}\begin{bmatrix}
 +
          (-2)^k & 0 \\
 +
          0 & (-3)^k 
 +
        \end{bmatrix} \begin{bmatrix}
 +
          -2 & 3 \\
 +
          2 & -4 
 +
        \end{bmatrix}}\\
 +
&&\\
 +
& = & \displaystyle{\begin{bmatrix}
 +
          2 & \frac{3}{2} \\
 +
          1 & 1 
 +
        \end{bmatrix}\begin{bmatrix}
 +
          (-2)^{k+1} & 3(-2)^k \\
 +
          2(-3)^k & (-4)(-3)^k 
 +
        \end{bmatrix}} \\
 +
&&\\
 +
& = & \displaystyle{\begin{bmatrix}
 +
          2(-2)^{k+1}+3(-3)^k & 6(-2)^k+-6(-3)^k \\
 +
          (-2)^{k+1}+2(-3)^k & 3(-2)^k+(-4)(-3)^k 
 +
        \end{bmatrix}.} \\
 +
\end{array}</math>
 
|}
 
|}
  
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!Final Answer: &nbsp;  
 
!Final Answer: &nbsp;  
 
|-
 
|-
 +
|&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{bmatrix}
 +
          2(-2)^{k+1}+3(-3)^k & 6(-2)^k+-6(-3)^k \\
 +
          (-2)^{k+1}+2(-3)^k & 3(-2)^k+(-4)(-3)^k 
 +
        \end{bmatrix}</math>
 
|&nbsp;&nbsp; &nbsp; &nbsp;   
 
|&nbsp;&nbsp; &nbsp; &nbsp;   
 
|}
 
|}
 
[[031_Review_Part_3|'''<u>Return to Sample Exam</u>''']]
 
[[031_Review_Part_3|'''<u>Return to Sample Exam</u>''']]

Revision as of 17:01, 13 October 2017

Find a formula for    by diagonalizing the matrix.


Foundations:  
Recall:
1. To diagonalize a matrix, you need to know the eigenvalues of the matrix.
2. Diagonalization Theorem
An    matrix    is diagonalizable if and only if    has    linearly independent eigenvectors.
In fact,    with    a diagonal matrix, if and only if the columns of    are    linearly
independent eigenvectors of    In this case, the diagonal entries of    are eigenvalues of    that
correspond, respectively , to the eigenvectors in  


Solution:

Step 1:  
To diagonalize this matrix, we need to find the eigenvalues and a basis for each eigenspace.
First, we find the eigenvalues of    by solving  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\text{det }}(A-\lambda I)=0.}
       Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\begin{array}{rcl}\displaystyle {{\text{det }}(A-\lambda I)}&=&\displaystyle {{\text{det }}{\bigg (}{\begin{bmatrix}1&-6\\2&-6\end{bmatrix}}-{\begin{bmatrix}\lambda &0\\0&\lambda \end{bmatrix}}{\bigg )}}\\&&\\&=&\displaystyle {{\text{det }}{\bigg (}{\begin{bmatrix}1-\lambda &-6\\2&-6-\lambda \end{bmatrix}}{\bigg )}}\\&&\\&=&\displaystyle {(1-\lambda )(-6\lambda )+12}\\&&\\&=&\displaystyle {\lambda ^{2}+5\lambda +6}\\&&\\&=&\displaystyle {(\lambda +2)(\lambda +3).}\\\end{array}}}
Therefore, setting
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle (\lambda +2)(\lambda +3)=0,}  
we find that the eigenvalues of    are    and  
Step 2:  
Now, we find a basis for each eigenspace by solving    for each eigenvalue  
For the eigenvalue  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \lambda =-2,}   we have

       Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\begin{array}{rcl}\displaystyle {A+2I}&=&\displaystyle {{\begin{bmatrix}1&-6\\2&-6\end{bmatrix}}+{\begin{bmatrix}2&0\\0&2\end{bmatrix}}}\\&&\\&=&\displaystyle {\begin{bmatrix}3&-6\\2&-4\end{bmatrix}}\\&&\\&\sim &\displaystyle {{\begin{bmatrix}1&-2\\0&0\end{bmatrix}}.}\end{array}}}

We see that    is a free variable. So, a basis for the eigenspace corresponding to    is
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\bigg \{}{\begin{bmatrix}2\\1\\\end{bmatrix}}{\bigg \}}.}
Step 3:  
For the eigenvalue  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \lambda =-3,}   we have

       

We see that    is a free variable. So, a basis for the eigenspace corresponding to    is
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\bigg \{}{\begin{bmatrix}{\frac {3}{2}}\\1\\\end{bmatrix}}{\bigg \}}.}
Step 4:  
To diagonalize our matrix, we use the information from the steps above.

Using the Diagonalization Theorem, we have  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle A=PDP^{-1}}   where

Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle D={\begin{bmatrix}-2&0\\0&-3\end{bmatrix}},P={\begin{bmatrix}2&{\frac {3}{2}}\\1&1\end{bmatrix}}.}
Step 5:  
Notice that

       


Final Answer:  
       Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\begin{bmatrix}2(-2)^{k+1}+3(-3)^{k}&6(-2)^{k}+-6(-3)^{k}\\(-2)^{k+1}+2(-3)^{k}&3(-2)^{k}+(-4)(-3)^{k}\end{bmatrix}}}       

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