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

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!Step 1:    
 
!Step 1:    
 
|-
 
|-
|
+
|Since &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is a triangular matrix, the eigenvalues are the entries on the diagonal.
 +
|-
 +
|Hence, the only eigenvalue of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is &nbsp;<math style="vertical-align: 0px">5.</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, to find a basis for the eigenspace corresponding to &nbsp;<math style="vertical-align: -4px">5,</math>&nbsp; we need to solve &nbsp;<math style="vertical-align: -5px">(A-5I)\vec{x}=\vec{0}.</math>
 +
|-
 +
|To do this, we use row reduction. Thus, we get
 +
|-
 +
|&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{array}{rcl}
 +
\displaystyle{A-5I} & = & \displaystyle{\begin{bmatrix}
 +
          5 & 1 \\
 +
          0 & 5
 +
        \end{bmatrix}-\begin{bmatrix}
 +
          5 & 0 \\
 +
          0 & 5
 +
        \end{bmatrix}}\\
 +
&&\\
 +
& \sim & \displaystyle{\begin{bmatrix}
 +
          0 & 1 \\
 +
          0 & 0
 +
        \end{bmatrix}.}
 +
\end{array}</math>
 +
|-
 +
|Solving this system, we see &nbsp;<math style="vertical-align: -4px">x_1</math>&nbsp; is a free variable and &nbsp;<math style="vertical-align: -4px">x_2=0.</math>
 +
|-
 +
|Therefore, a basis for this eigenspace is
 
|-
 
|-
 
|
 
|
 +
::<math>\bigg\{\begin{bmatrix}
 +
          1  \\
 +
          0 
 +
        \end{bmatrix}\bigg\}.</math>
 
|}
 
|}
  
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!Final Answer: &nbsp;  
 
!Final Answer: &nbsp;  
 
|-
 
|-
|&nbsp;&nbsp; '''(a)''' &nbsp; &nbsp;  
+
|&nbsp;&nbsp; '''(a)''' &nbsp; &nbsp; The only eigenvalue of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is &nbsp;<math style="vertical-align: 0px">5</math>&nbsp; and the corresponding eigenspace has basis &nbsp;<math style="vertical-align: -20px">\bigg\{\begin{bmatrix}
 +
          1  \\
 +
          0 
 +
        \end{bmatrix}\bigg\}.</math>
 +
 
 
|-
 
|-
 
|&nbsp;&nbsp; '''(b)''' &nbsp; &nbsp;  
 
|&nbsp;&nbsp; '''(b)''' &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 15:56, 13 October 2017

Let  

(a) Find a basis for the eigenspace(s) of  

(b) Is the matrix    diagonalizable? Explain.


Foundations:  
Recall:
1. The eigenvalues of a triangular matrix are the entries on the diagonal.
2. By the Diagonalization Theorem, an    matrix    is diagonalizable
if and only if    has    linearly independent eigenvectors.


Solution:

(a)

Step 1:  
Since    is a triangular matrix, the eigenvalues are the entries on the diagonal.
Hence, the only eigenvalue of    is  
Step 2:  
Now, to find a basis for the eigenspace corresponding to    we need to solve  
To do this, we use row reduction. Thus, we get
       
Solving this system, we see    is a free variable and  
Therefore, a basis for this eigenspace is

(b)

Step 1:  
Step 2:  


Final Answer:  
   (a)     The only eigenvalue of    is    and the corresponding eigenspace has basis  
   (b)    

Return to Sample Exam