Description
1. A linear transformation T : R3 ! R3 has an eigenvector 4 0 5 associated with eigenvalue 1=4 and two
2
2 3 2 3
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1
eigenvectors 4 15 and 4 15 both associated with eigenvalue 3. Answer all of the following questions
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9
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without finding the matrix for T .
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Identify the image of following vectors under the transformation T . Be sure to justify your conclu-sions.
2 3 2 3
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1=2
(i) 4 0 5 (ii) 4 1=25
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9=2
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(b) Explain why T
02
35
31
=
3
2
35
3
.
@4
37
5A
4
37
5
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31
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1
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Calculate T @4 25A. 12
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Let T : R2 ! R2 be the linear transformation that reflects the entire R2 across the x-axis.
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Without calculating a matrix A for the transformation T , determine what the eigenvectors and eigen-values would be, if any. In other words, does the transformation have any stretch directions and associated stretch factors? Justify your answer.
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Find a matrix A to represent the transformation T . Calculate its eigenvectors and associated eigen-values for the matrix A, and verify your answers to part (a).
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3
1 1 1
3. Let A = 41 |
1 |
1 |
5. |
1 |
1 |
1 |
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(Strang x5.2 #3) Without solving det(A I) = 0, use observation to find all eigenvalues of A and then find associated eigenvectors.
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Hint 1. What can you say about the rank of A and what does that tell you about the nullspace? What does nullspace have to do with eigen-theory?
Hint 2. Note that the rows of A add up to the same number 3, which would lead you to another eigenvector-eigenvalue pair.
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Compute A100 by diagonalizing A.
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A is an n n matrix.
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(Strang x5.1 #23) Fill in the blanks.
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i.
If you know ~x is an eigenvector of A, the way to find the associated eigenvalue is to
.
ii.
f you know is an eigenvalue of A, the way to find an associated eigenvector is to
.
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(Strang x5.1 #24) Let be an eigenvalue of A with associated eigenvecter ~x. That is, A~x = ~x. Use part
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as a hint to prove the following statements.
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2 is an eigenvalue of A2. (Also review problem #6 of Homework 11.)
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If A is invertible, 1 is an eigenvalue of A 1.
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+ 1 is an eigenvalue of A + I.
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