Difference between revisions of "031 Review Part 3, Problem 7"

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!Foundations:    
 
!Foundations:    
 
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|'''Diagonalization Theorem'''
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|An &nbsp;<math style="vertical-align: 0px">n\times n</math>&nbsp; matrix &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is diagonalizable if and only if &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; has &nbsp;<math style="vertical-align: 0px">n</math>&nbsp; linearly independent eigenvectors.
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|In fact, &nbsp;<math style="vertical-align: -4px">A=PDP^{-1},</math>&nbsp; with &nbsp;<math style="vertical-align: 0px">D</math>&nbsp; a diagonal matrix, if and only if the columns of &nbsp;<math style="vertical-align: 0px">P</math>&nbsp; are &nbsp;<math style="vertical-align: 0px">n</math>&nbsp; linearly
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|independent eigenvectors of &nbsp;<math style="vertical-align: 0px">A.</math>&nbsp; In this case, the diagonal entries of &nbsp;<math style="vertical-align: 0px">D</math>&nbsp; are eigenvalues of &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; that
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|correspond, respectively , to the eigenvectors in &nbsp;<math style="vertical-align: 0px">P.</math>
 
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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:  
Step 2:  


Final Answer:  
      

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