Difference between revisions of "031 Review Part 3, Problem 7"
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!Foundations: | !Foundations: | ||
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− | | | + | |'''Diagonalization Theorem''' |
+ | |- | ||
+ | |An <math style="vertical-align: 0px">n\times n</math> matrix <math style="vertical-align: 0px">A</math> is diagonalizable if and only if <math style="vertical-align: 0px">A</math> has <math style="vertical-align: 0px">n</math> linearly independent eigenvectors. | ||
+ | |- | ||
+ | |In fact, <math style="vertical-align: -4px">A=PDP^{-1},</math> with <math style="vertical-align: 0px">D</math> a diagonal matrix, if and only if the columns of <math style="vertical-align: 0px">P</math> are <math style="vertical-align: 0px">n</math> linearly | ||
+ | |- | ||
+ | |independent eigenvectors of <math style="vertical-align: 0px">A.</math> In this case, the diagonal entries of <math style="vertical-align: 0px">D</math> are eigenvalues of <math style="vertical-align: 0px">A</math> that | ||
+ | |- | ||
+ | |correspond, respectively , to the eigenvectors in <math style="vertical-align: 0px">P.</math> | ||
|} | |} | ||
Revision as of 10:21, 13 October 2017
Let
Use the Diagonalization Theorem to find the eigenvalues of and a basis for each eigenspace.
Foundations: |
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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: |
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Step 2: |
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Final Answer: |
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