Matrix A is factored in the form PDP-1. Use the Diagonalization Theorem to find the eigenvalues of A and a basis for each eigenspace. A = 20-12 6 5 24 5 00 -4 0-1 = 0 1 2 1 00 500 0 0 1 050 2 1 8 002 -1 0-4

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter4: Eigenvalues And Eigenvectors
Section4.5: Iterative Methods For Computing Eigenvalues
Problem 16EQ
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Matrix A is factored in the form PDP-1. Use the Diagonalization Theorem to find the eigenvalues of A and a basis for
each eigenspace.
A =
20 - 12
65 24
00 5
=
1
- 4 0
0 1 2
1 00
500
050
002
0 0 1
2 1 8
-1 0-4
Select the correct choice below and fill in the answer boxes to complete your choice.
(Use a comma to separate vectors as needed.)
A. There is one distinct eigenvalue, λ =
A basis for the corresponding eigenspace is
and 2₂
=
=
B. In ascending order, the two distinct eigenvalues are ₁
eigenspaces are and respectively.
C. In ascending order, the three distinct eigenvalues are ₁ = ₂ =
corresponding eigenspaces are 4., and }, respectively.
3
Bases for the corresponding
and 3
=
Bases for the
Transcribed Image Text:Matrix A is factored in the form PDP-1. Use the Diagonalization Theorem to find the eigenvalues of A and a basis for each eigenspace. A = 20 - 12 65 24 00 5 = 1 - 4 0 0 1 2 1 00 500 050 002 0 0 1 2 1 8 -1 0-4 Select the correct choice below and fill in the answer boxes to complete your choice. (Use a comma to separate vectors as needed.) A. There is one distinct eigenvalue, λ = A basis for the corresponding eigenspace is and 2₂ = = B. In ascending order, the two distinct eigenvalues are ₁ eigenspaces are and respectively. C. In ascending order, the three distinct eigenvalues are ₁ = ₂ = corresponding eigenspaces are 4., and }, respectively. 3 Bases for the corresponding and 3 = Bases for the
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