In looking for a proof to the Gerschgorin's Theorem, I stumbled across this paper: http://buzzard.ups.edu/courses/2007spring/projects/brakkenthal-paper.pdf
I don't quite buy the proof for Theorem 2.1 in that paper (yet).
Theorem 2.1: every eigenvalue $\lambda$ of a square matrix $A\in \mathbb{C}^{n\times n}$ satisfies $$ \vert \lambda - A_{ii}\vert \leq \sum_{j\neq i}\vert A_{i,j}\vert , i\in \{1,2,\ldots,n\} $$
And the proof offered:
If Theorem 2.1 is not satisfied, then $\lambda I-A$ is strictly diagonally dominant (SDD).
$\Rightarrow$ $\lambda I - A$ is non-singular
$\Rightarrow$ $\lambda$ is not an eigenvalue of $A$
My problem lies with
Theorem not satisfied $\Rightarrow$ $\lambda I - A$ is SDD
part.
I mean, the author also states that
the matrix $\lambda I - A$ is SDD if $\vert \lambda - A_{ii}\vert > \sum_{j\neq i}\vert A_{i,j}\vert$ for every i
But the way I see it, the theorem is already not satisfied if $$\vert \lambda - A_{ii}\vert > \sum_{j\neq i}\vert A_{i,j}\vert$$ were to hold for some $i$ while $$\vert \lambda - A_{kk}\vert \leq \sum_{j\neq k}\vert A_{k,j}\vert$$ for some $k\neq i$, in which case $\lambda I - A$ would not be SDD.
What am I missing?