True or Flase Statements
Chapter 1 Eigenvalues and Eigenvectors
- A matrix and its inverse have the same eigen values if A is orthogonal.
- Two linearly independent eigenvectors may correspond to an eigenvalue λ of a matrix.
- Cayley–Hamilton Theorem is applicable to every matrix.
- A square matrix with repeated eigenvalues is not diagonalizable.
- Powers of a square matrix can be found using diagonalization.
- Every real square matrix can be uniquely expressed as the sum of a symmetric and a skew-symmetric matrix.
- If A and B are symmetric then AB is symmetric.
Chapter 2 Quadratic Forms
- If A is a symmetric matrix with distinct eigenvalues then its eigenvectors are orthogonal.
- A square matrix with two ...
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