Chapter 6: Problem 6
Let \(A\) be a diagonalizable matrix whose eigenvalues are all either 1 or \(-1 .\) Show that \(A^{-1}=A\)
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Chapter 6: Problem 6
Let \(A\) be a diagonalizable matrix whose eigenvalues are all either 1 or \(-1 .\) Show that \(A^{-1}=A\)
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Show that if \(\sigma\) is a singular value of \(A,\) then there exists a nonzero vector x such that \\[ \sigma=\frac{\|A \mathbf{x}\|_{2}}{\|\mathbf{x}\|_{2}} \\]
Let \(A\) be an \(n \times n\) matrix with singular values \(\sigma_{1}, \sigma_{2}, \ldots, \sigma_{n}\) and eigenvalues \(\lambda_{1}, \lambda_{2}, \ldots, \lambda_{n} .\) Show that \\[ \left|\lambda_{1} \lambda_{2} \cdots \lambda_{n}\right|=\sigma_{1} \sigma_{2} \cdots \sigma_{n} \\]
Show that if a matrix \(U\) is both unitary and Hermitian, then any eigenvalue of \(U\) must equal either 1 or -1
Let \(A\) be a singular \(n \times n\) matrix. Show that \(A^{T} A\) is positive semidefinite, but not positive definite.
Let \(A\) be a \(4 \times 4\) matrix and let \(\lambda\) be an eigenvalue of multiplicity 3. If \(A-\lambda I\) has rank 1 , is \(A\) defective? Explain.
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