Suppose that A and B are n x n matrices. Which of the following statements is(are) correct? Statements b and d a)lf 0 is an eigenvalue of A, then A is invertible b)The zero vector is in the eigenspace of A associated with an eigenvalue Statements a, b and d c)The matrix A and its transpose AT have different sets of eigenvalues. O d)lf 4 is an eigenvalue of A, then A - 4I is not invertible Statements b, c and d
Suppose that A and B are n x n matrices. Which of the following statements is(are) correct? Statements b and d a)lf 0 is an eigenvalue of A, then A is invertible b)The zero vector is in the eigenspace of A associated with an eigenvalue Statements a, b and d c)The matrix A and its transpose AT have different sets of eigenvalues. O d)lf 4 is an eigenvalue of A, then A - 4I is not invertible Statements b, c and d
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Transcribed Image Text:Suppose that A and B are n x n matrices. Which of the following statements is(are) correct?
Statements b and d
a)lf 0 is an eigenvalue of A, then A is invertible
O b)The zero vector is in the eigenspace of A associated with an eigenvalue >
O
Statements a, b and d
O c)The matrix A and its transpose AT have different sets of eigenvalues.
d)lf 4 is an eigenvalue of A, then A - 4I is not invertible
O Statements b, c and d
A
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Transcribed Image Text:Suppose that A and B are n x n matrices. Which of the following statements is (are) false?
O d) The multiplicity of a root r of the characteristic equation of A is called the algebraic multiplicity of r as an eigenvalue n
a)lf A-7 is a factor of the characteristic of A, then 7 is an eigenvalue of A
Statements b, d and e
O Statements b, c and e
O Statements a, b and e
O Statements b and e
O e) If two matrices have the same set of eigenvalues, then they are similar
O c)The eigenvalue of the n x n identity matrix is 1 with algebraic multiplicity n
O b)A matrix A can have more than n eigenvalues
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