Difference between revisions of "031 Review Part 3, Problem 2"

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(Created page with "<span class="exam">Consider the matrix  <math style="vertical-align: -31px">A= \begin{bmatrix} 1 & -4 & 9 & -7 \\ -1 & 2 & -4 & 1 \\...")
 
 
(4 intermediate revisions by the same user not shown)
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<span class="exam">Consider the matrix &nbsp;<math style="vertical-align: -31px">A=     
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<span class="exam"> Find the eigenvalues and eigenvectors of the matrix &nbsp;<math style="vertical-align: -31px">A=     
 
     \begin{bmatrix}
 
     \begin{bmatrix}
           1 & -4 & 9 & -7 \\
+
           1 & 1 & 1 \\
          -1 & 2  & -4 & 1 \\
+
           0 & -1  & 1 \\
           5 & -6 & 10 & 7
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           0 & 0 & 2
        \end{bmatrix}</math>&nbsp; and assume that it is row equivalent to the matrix
+
         \end{bmatrix}.</math>
 
 
::<math>B=   
 
    \begin{bmatrix}
 
          1 & 0 & -1 & 5 \\
 
          0 & -2 & 5 & -6 \\
 
           0 & 0 & 0 & 0
 
         \end{bmatrix}.</math>    
 
   
 
<span class="exam">(a) List rank &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; and &nbsp;<math style="vertical-align: 0px">\text{dim Nul }A.</math>
 
 
 
<span class="exam">(b) Find bases for &nbsp;<math style="vertical-align: 0px">\text{Col }A</math>&nbsp; and &nbsp;<math style="vertical-align: 0px">\text{Nul }A.</math>&nbsp; Find an example of a nonzero vector that belongs to &nbsp;<math style="vertical-align: -5px">\text{Col }A,</math>&nbsp; as well as an example of a nonzero vector that belongs to &nbsp;<math style="vertical-align: 0px">\text{Nul }A.</math>
 
 
 
  
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Foundations: &nbsp;  
 
!Foundations: &nbsp;  
 
|-
 
|-
|
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|An eigenvector of a matrix &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is a nonzero vector &nbsp;<math style="vertical-align: 0px">\vec{x}</math>&nbsp; such that &nbsp;<math style="vertical-align: 0px">A\vec{x}=\lambda\vec{x}</math>&nbsp; for some scalar &nbsp;<math style="vertical-align: 0px">\lambda.</math>
 +
|-
 +
|In this case, we say that &nbsp;<math style="vertical-align: 0px">\lambda</math>&nbsp; is an eigenvalue of &nbsp;<math style="vertical-align: 0px">A.</math>
 
|}
 
|}
  
  
 
'''Solution:'''
 
'''Solution:'''
 
'''(a)'''
 
  
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Step 1: &nbsp;  
 
!Step 1: &nbsp;  
 
|-
 
|-
|
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|Since &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is a triangular matrix, the eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; are the entries on the diagonal.
 +
|-
 +
|So, the eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; are &nbsp;<math style="vertical-align: -4px">1,-1,</math>&nbsp; and &nbsp;<math style="vertical-align: 0px">2.</math>
 
|}
 
|}
  
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!Step 2: &nbsp;
 
!Step 2: &nbsp;
 
|-
 
|-
|
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|Since the matrix is triangular and all the eigenvalues are distinct, the eigenvectors of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; are
|}
 
 
 
'''(b)'''
 
 
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Step 1: &nbsp;  
 
 
|-
 
|-
 
|
 
|
|}
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::<math>\begin{bmatrix}
 
+
          1  \\
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
+
          0 \\
!Step 2: &nbsp;
+
          0
 +
        \end{bmatrix},\begin{bmatrix}
 +
          0  \\
 +
          1 \\
 +
          0
 +
        \end{bmatrix},\begin{bmatrix}
 +
          0  \\
 +
          0 \\
 +
          1
 +
        \end{bmatrix}</math>
 
|-
 
|-
|
+
|where each eigenvector has eigenvalue &nbsp;<math style="vertical-align: -4px">1,-1</math>&nbsp; and &nbsp;<math style="vertical-align: -4px">2,</math>&nbsp; respectively.
 
|}
 
|}
  
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!Final Answer: &nbsp;  
 
!Final Answer: &nbsp;  
 
|-
 
|-
|&nbsp;&nbsp; '''(a)''' &nbsp; &nbsp;  
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|&nbsp;&nbsp; &nbsp; &nbsp; The eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; are &nbsp;<math style="vertical-align: -4px">1,-1</math>&nbsp; and &nbsp;<math style="vertical-align: -4px">2,</math>&nbsp; and the corresponding eigenvectors are
 
|-
 
|-
|&nbsp;&nbsp; '''(b)''' &nbsp; &nbsp;
+
|
 +
::<math>\begin{bmatrix}
 +
          1  \\
 +
          0 \\
 +
          0
 +
        \end{bmatrix},\begin{bmatrix}
 +
          0  \\
 +
          1 \\
 +
          0
 +
        \end{bmatrix},\begin{bmatrix}
 +
          0  \\
 +
          0 \\
 +
          1
 +
        \end{bmatrix}.</math>
 
|}
 
|}
[[031_Review_Part_3|'''<u>Return to Sample Exam</u>''']]
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[[031_Review_Part_3|'''<u>Return to Review Problems</u>''']]

Latest revision as of 13:53, 15 October 2017

Find the eigenvalues and eigenvectors of the matrix  

Foundations:  
An eigenvector of a matrix    is a nonzero vector    such that    for some scalar  
In this case, we say that    is an eigenvalue of  


Solution:

Step 1:  
Since    is a triangular matrix, the eigenvalues of    are the entries on the diagonal.
So, the eigenvalues of    are    and  
Step 2:  
Since the matrix is triangular and all the eigenvalues are distinct, the eigenvectors of    are
where each eigenvector has eigenvalue    and    respectively.


Final Answer:  
       The eigenvalues of    are    and    and the corresponding eigenvectors are

Return to Review Problems