Difference between revisions of "031 Review Part 3, Problem 7"

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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=  
+
<span class="exam">Let &nbsp;<math>A=\begin{bmatrix}
    \begin{bmatrix}
+
           3 & 0 & -1 \\
           1 & -4 & 9 & -7 \\
+
           0 & 1 &-3\\
           -1 & 2  & -4 & 1 \\
+
           1 & 0 & 0
           5 & -6 & 10 & 7
+
         \end{bmatrix}\begin{bmatrix}
         \end{bmatrix}</math>&nbsp; and assume that it is row equivalent to the matrix
+
           3 & 0 & 0 \\
 
+
           0 & 4 &0\\
::<math>B=   
+
           0 & 0 & 3
    \begin{bmatrix}
+
         \end{bmatrix}\begin{bmatrix}
           1 & 0 & -1 & 5 \\
+
          0 & 0 & 1 \\
           0 & -2  & 5 & -6 \\
+
          -3 & 1 &9\\
           0 & 0 & 0 & 0
+
          -1 & 0 & 3
         \end{bmatrix}.</math>     
+
        \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>
 
  
 +
<span class="exam">Use the Diagonalization Theorem to find the eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; and a basis for each eigenspace.
  
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Foundations: &nbsp;  
 
!Foundations: &nbsp;  
 
|-
 
|-
|
+
|'''Diagonalization Theorem'''
 +
|-
 +
|An &nbsp;<math style="vertical-align: 0px">n\times n</math>&nbsp; matrix &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is diagonalizable if and only if &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; has &nbsp;<math style="vertical-align: 0px">n</math>&nbsp; linearly independent eigenvectors.
 +
|-
 +
|In fact, &nbsp;<math style="vertical-align: -4px">A=PDP^{-1},</math>&nbsp; with &nbsp;<math style="vertical-align: 0px">D</math>&nbsp; a diagonal matrix, if and only if the columns of &nbsp;<math style="vertical-align: 0px">P</math>&nbsp; are &nbsp;<math style="vertical-align: 0px">n</math>&nbsp; linearly
 +
|-
 +
|independent eigenvectors of &nbsp;<math style="vertical-align: 0px">A.</math>&nbsp; In this case, the diagonal entries of &nbsp;<math style="vertical-align: 0px">D</math>&nbsp; are eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; that
 +
|-
 +
|correspond, respectively , to the eigenvectors in &nbsp;<math style="vertical-align: 0px">P.</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;  
 +
|-
 +
|Since
 
|-
 
|-
 
|
 
|
 +
::<math>\begin{bmatrix}
 +
          3 & 0 & 0 \\
 +
          0 & 4 &0\\
 +
          0 & 0 & 3
 +
        \end{bmatrix}</math>
 +
|-
 +
|is a diagonal matrix, the eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; are &nbsp;<math style="vertical-align: 0px">3</math>&nbsp; and &nbsp;<math style="vertical-align: -1px">4</math>&nbsp; by the Diagonalization Theorem.
 
|}
 
|}
  
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Step 2: &nbsp;
 
!Step 2: &nbsp;
 +
|-
 +
|By the Diagonalization Theorem, a basis for the eigenspace corresponding
 +
|-
 +
|to the eigenvalue &nbsp;<math style="vertical-align: 0px">3</math>&nbsp; is
 
|-
 
|-
 
|
 
|
|}
+
::<math>\Bigg\{\begin{bmatrix}
 
+
          3 \\
'''(b)'''
+
          0 \\
 
+
          1
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
+
        \end{bmatrix},\begin{bmatrix}
!Step 1: &nbsp;
+
          -1 \\
 +
          -3\\
 +
          0
 +
        \end{bmatrix}\Bigg\}</math>
 
|-
 
|-
|
+
|and a basis for the eigenspace corresponding to the eigenvalue &nbsp;<math style="vertical-align: -1px">4</math>&nbsp; is
|}
 
 
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
!Step 2: &nbsp;
 
 
|-
 
|-
 
|
 
|
 +
::<math>\Bigg\{\begin{bmatrix}
 +
          0 \\
 +
          1 \\
 +
          1
 +
        \end{bmatrix}\Bigg\}.</math>
 
|}
 
|}
  
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!Final Answer: &nbsp;  
 
!Final Answer: &nbsp;  
 
|-
 
|-
|&nbsp;&nbsp; '''(a)''' &nbsp; &nbsp;  
+
|&nbsp; &nbsp; &nbsp; &nbsp; The eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; are &nbsp;<math style="vertical-align: 0px">3</math>&nbsp; and &nbsp;<math style="vertical-align: -1px">4.</math>&nbsp;
 +
|-
 +
|&nbsp; &nbsp; &nbsp; &nbsp; A basis for the eigenspace corresponding
 +
|-
 +
|&nbsp; &nbsp; &nbsp; &nbsp; to the eigenvalue &nbsp;<math style="vertical-align: 0px">3</math>&nbsp; is
 
|-
 
|-
|&nbsp;&nbsp; '''(b)''' &nbsp; &nbsp;  
+
|
 +
::::<math>\Bigg\{\begin{bmatrix}
 +
          3 \\
 +
          0 \\
 +
          1
 +
        \end{bmatrix},\begin{bmatrix}
 +
          -1 \\
 +
          -3\\
 +
          0
 +
        \end{bmatrix}\Bigg\}</math>
 +
|-
 +
|&nbsp; &nbsp; &nbsp; &nbsp; and a basis for the eigenspace corresponding to the eigenvalue &nbsp;<math style="vertical-align: -1px">4</math>&nbsp; is
 +
|-
 +
|
 +
::::<math>\Bigg\{\begin{bmatrix}
 +
          0 \\
 +
          1 \\
 +
          1
 +
        \end{bmatrix}\Bigg\}.</math>
 
|}
 
|}
[[031_Review_Part_3|'''<u>Return to Sample Exam</u>''']]
+
[[031_Review_Part_3|'''<u>Return to Review Problems</u>''']]

Latest revision as of 14:03, 15 October 2017

Let  

Use the Diagonalization Theorem to find the eigenvalues of    and a basis for each eigenspace.

Foundations:  
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:  
Since
is a diagonal matrix, the eigenvalues of    are    and    by the Diagonalization Theorem.
Step 2:  
By the Diagonalization Theorem, a basis for the eigenspace corresponding
to the eigenvalue    is
and a basis for the eigenspace corresponding to the eigenvalue    is


Final Answer:  
        The eigenvalues of    are    and   
        A basis for the eigenspace corresponding
        to the eigenvalue    is
        and a basis for the eigenspace corresponding to the eigenvalue    is

Return to Review Problems