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Matrix norm is defined as

\begin{aligned}\|A\|&=\sup \left\{{\frac {\|Ax\|}{\|x\|}}:x\in K^{n}{\text{ with }}x\neq 0\right\}.\end{aligned}

How can we derive the following calculating formulas

\begin{aligned}\|A\|_{1}=\max _{1\leq j\leq n}\sum _{i=1}^{m}|a_{ij}|\end{aligned}

\begin{aligned}\|A\|_{\infty }=\max _{1\leq i\leq m}\sum _{j=1}^{n}|a_{ij}|\end{aligned}

\begin{aligned} \|A\|_{2}=\sigma _{\max }(A)\end{aligned}

jinge
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  • What do you man by 'derive'. These formulas define different norms. They are not equal to each other. – Kavi Rama Murthy Nov 16 '19 at 04:47
  • First two are easy: prove $\le$ and then find one that gives $=$. The last one are usually done via SVD and the unitary invariance of the 2-norm. – A.Γ. Nov 16 '19 at 05:12
  • Yes, I know the formulas defines different norms. I want to know how to prove them respectively. – jinge Nov 16 '19 at 07:17
  • Can you give a brief provement for the first one? I have tried but not succeeded. – jinge Nov 16 '19 at 07:18

0 Answers0