Difference between revisions of "031 Review Part 3, Problem 3"
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<span class="exam">(b) Is the matrix <math style="vertical-align: 0px">A</math> diagonalizable? Explain. | <span class="exam">(b) Is the matrix <math style="vertical-align: 0px">A</math> diagonalizable? Explain. | ||
− | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
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|Now, to find a basis for the eigenspace corresponding to <math style="vertical-align: -4px">5,</math> we need to solve <math style="vertical-align: -5px">(A-5I)\vec{x}=\vec{0}.</math> | |Now, to find a basis for the eigenspace corresponding to <math style="vertical-align: -4px">5,</math> we need to solve <math style="vertical-align: -5px">(A-5I)\vec{x}=\vec{0}.</math> | ||
|- | |- | ||
− | | | + | |We have |
|- | |- | ||
| <math>\begin{array}{rcl} | | <math>\begin{array}{rcl} | ||
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\end{bmatrix}}\\ | \end{bmatrix}}\\ | ||
&&\\ | &&\\ | ||
− | & | + | & = & \displaystyle{\begin{bmatrix} |
0 & 1 \\ | 0 & 1 \\ | ||
0 & 0 | 0 & 0 | ||
Line 74: | Line 73: | ||
!Step 1: | !Step 1: | ||
|- | |- | ||
− | | | + | |From part (a), we know that <math style="vertical-align: 0px">A</math> only has one linearly independent eigenvector. |
|} | |} | ||
Line 80: | Line 79: | ||
!Step 2: | !Step 2: | ||
|- | |- | ||
− | | | + | |By the Diagonalization Theorem, <math style="vertical-align: 0px">A</math> must have <math style="vertical-align: 0px">2</math> linearly independent eigenvectors to be diagonalizable. |
+ | |- | ||
+ | |Hence, <math style="vertical-align: 0px">A</math> is not diagonalizable. | ||
|} | |} | ||
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|- | |- | ||
− | | '''(b)''' | + | | '''(b)''' <math style="vertical-align: 0px">A</math> is not diagonalizable. |
|} | |} | ||
− | [[031_Review_Part_3|'''<u>Return to | + | [[031_Review_Part_3|'''<u>Return to Review Problems</u>''']] |
Latest revision as of 13:54, 15 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 |
|
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: |
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Now, to find a basis for the eigenspace corresponding to we need to solve |
We have |
Solving this system, we see is a free variable and |
Therefore, a basis for this eigenspace is |
|
(b)
Step 1: |
---|
From part (a), we know that only has one linearly independent eigenvector. |
Step 2: |
---|
By the Diagonalization Theorem, must have linearly independent eigenvectors to be diagonalizable. |
Hence, is not diagonalizable. |
Final Answer: |
---|
(a) The only eigenvalue of is and the corresponding eigenspace has basis |
(b) is not diagonalizable. |