Difference between revisions of "031 Review Part 3, Problem 7"
		
		
		
		
		
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| Kayla Murray (talk | contribs) | Kayla Murray (talk | contribs)  | ||
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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: | 
|---|
| 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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