# Tagged Questions

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### Special Matrix 2-norm and F-norm Inequalities

This is a homework problem for my Numerical Linear Algebra course. It states the following: If A is an mxm nonsingular matrix, prove the following: (1)$\|A+(A^{*})^{-1}\| _{2} \ge 2$ ...
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### Relation between condition number and perturbed matrix

Prove that if $A\vec{x} = \vec{b}$ and $(A+\delta{}A)(\vec{x}+\delta\vec{x}) = \vec{b}$, then $\dfrac{\|\delta\vec{x}\|/\|\vec{x}+\delta\vec{x}\|}{\|\delta{}A\|/\|A\|} \le \kappa{(A)}$, where ...
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### How to tell if two matrices are equal up to a permutation

Given two real rectangular matrices A, B how can I tell if they are equal up to a permutation of their rows/column without trying all possible permutations? (This is closely related to the question I ...
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### How to find 2x2 matrix with non zero elements and repeated eigenvalues?

I need to find a 2x2 matrix with non zero elements that has eigenvalue = 1 repeated (double). How can i do that? Thanks!
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### Differences between methods for solving linear equation system

I have a huge linear equation system in this form: F=K.Î” as usual form of problems in the finite element method, where the F vector and K are known and Î” vector is unknown. There are several ...
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### Need matlab help to construct a numerical example for solving system of linear equation for random matrices

I am reading this paper(page 183). In this paper the iterative methods for computing some solution of the general restricted linear equations \begin{eqnarray} Ax = b, ~~~~ x\in R(A^{k})~~~~ b\in ...
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### Understanding higher order SVD

Can someone explain the singular value decomposition of a tensor (maybe a 3 dimensional matrix) with an example? It is intuitively difficult to the get the meaning from just the formulas. On a ...
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### cube root of positive definite matrix

Suppose that $A$ is a real symmetric positive definite $20\times 20$ matrix with condition number $\kappa\le 1000$. I want to solve the system of linear equations $$A^{1/3}x=b$$ with $10$-digit ...
### Proof $\langle Ax,y\rangle = \langle x,A^*y\rangle$ when $A$ Hermitian
I was trying to understand a proof of why a Hermitian $A$ matrix has its eigenvectors orthogonal. As part of the proof they state $$\langle Ax,y\rangle = \langle x,A^*y\rangle$$ From which property ...