Difference between revisions of "031 Review Part 3, Problem 3"
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!Step 1: | !Step 1: | ||
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− | | | + | |From part (a), we know that <math style="vertical-align: 0px">A</math> only has one linearly independent eigenvector. |
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!Step 2: | !Step 2: | ||
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− | | | + | |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. |
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+ | |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. |
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[[031_Review_Part_3|'''<u>Return to Sample Exam</u>''']] | [[031_Review_Part_3|'''<u>Return to Sample Exam</u>''']] |
Revision as of 16:06, 13 October 2017
Let
(a) Find a basis for the eigenspace(s) of
(b) Is the matrix diagonalizable? Explain.
Foundations: |
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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 |
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: |
---|
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: |
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(a) The only eigenvalue of is and the corresponding eigenspace has basis |
(b) is not diagonalizable. |