# Tagged Questions

Linear algebra is concerned with vector spaces of all dimensions and linear transformations between them, including systems of linear equations, bases, dimensions, subspaces, matrices, determinants, traces, eigenvalues and eigenvectors, diagonalization, Jordan forms, etc. For questions specifically ...

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### Limit of the projection of a matrix when the projection is not continuous

Consider two real matrices: the $n\times n$ matrix $A$ the $n\times m$ matrix $B$ of rank $m$, with $m<n$. Let, for $a\in\mathbb{R}$, $$S_a=A-aI_n,$$ and denote by $P_a$ the orthogonal ...
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### Triangulation of matrices

Suppose that $A$ is some triangularizable matrix in $M_n(\mathbb R)$. The usual approach I know of to find a triangular matrix similar to it is to find bases for all the eigenspaces, then find their ...
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### How to differentiate between $(\lambda_{0}-\lambda)^{k} \,\text{and } g(\lambda) \,\text{in } f_{A}(\lambda)$?

By definition, $\lambda_{0}$ has algebraic multiplicity $k$ if $\lambda_{0}$ is a root of $f_{A}(\lambda)=(\lambda_{0}-\lambda)^{k}g(\lambda)$. What am I missing from this? ...
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### Relationships between affine closures and convex closures

Let $V$ denote a vector space. Then the following concepts make sense: affine subset of $V$ affine closure (affine "hull") of a subset of $V$ Suppose $V$ is in fact a real vector space. Then the ...
### Proving rank of $AB$ is at most equal to rank of $B$
$A=m\times n$ matrix. $B = n\times p$ matrix. Prove that the rank of of the product $AB$ is at most equal to the rank of $B$. Current state of my work: (1) First idea: show that the kernel of $B$, ...
Let in the space $V$ defined norm $||\cdot||_V$ and in the space $W$ defined norm $||\cdot||_W$ Then consider operator norm induced by 2 vector norms $||\cdot||_V$ and $||\cdot||_W$ \$ ||A|| ...