4. True or False? If true, prove. If false, provide a counterexample. a. If same size matrices A and B have exactly the same eigenvalues (including multiplicities), they must be similar. b. If a square matrix A is diagonalizable, so is Ak, for any positive integer k. C. If a square invertible matrix A is diagonalizable, so is A-¹. d. If a square matrix A is invertible, then it's diagonalizable. e. For any m x n matrix A, the matrix AT A is orthogonally diagonalizable. f. Let A be a symmetric n x n matrix. Suppose ₁ and ₂ are eigenvectors corresponding to two distinct eigenvalues of A. Then, ||x₁ + x₂ || = ||X₁|| + ||x₂||. g. If an n x n matrix A has only real eigenvalues, then it must be symmetric.

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
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Chapter2: Second-order Linear Odes
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4. True or False? If true, prove. If false, provide a counterexample.
a. If same size matrices A and B have exactly the same eigenvalues (including multiplicities), they
must be similar.
b. If a square matrix A is diagonalizable, so is Ak, for any positive integer k.
C.
If a square invertible matrix A is diagonalizable, so is A-¹.
d. If a square matrix A is invertible, then it's diagonalizable.
e. For any m x n matrix A, the matrix AT A is orthogonally diagonalizable.
f.
Let A be a symmetric n x n matrix. Suppose ₁ and ₂ are eigenvectors corresponding to two
distinct eigenvalues of A. Then, ||x₁ + x₂ || = ||X₁|| + ||x₂||.
g.
If an n x n matrix A has only real eigenvalues, then it must be symmetric.
Transcribed Image Text:4. True or False? If true, prove. If false, provide a counterexample. a. If same size matrices A and B have exactly the same eigenvalues (including multiplicities), they must be similar. b. If a square matrix A is diagonalizable, so is Ak, for any positive integer k. C. If a square invertible matrix A is diagonalizable, so is A-¹. d. If a square matrix A is invertible, then it's diagonalizable. e. For any m x n matrix A, the matrix AT A is orthogonally diagonalizable. f. Let A be a symmetric n x n matrix. Suppose ₁ and ₂ are eigenvectors corresponding to two distinct eigenvalues of A. Then, ||x₁ + x₂ || = ||X₁|| + ||x₂||. g. If an n x n matrix A has only real eigenvalues, then it must be symmetric.
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