Prove that this is a norm, infimum norm

functional-analysisreal-analysis

I'm trying to prove that given a vector space $X$ of finite dimension, $U \subset X$ an open subset, bounded, convex and symmetric with respect to $\bar{0} \in X$ (that is if $x \in U \Rightarrow -x \in U$). Prove that

$|x|_{u} = inf \{ \lambda > 0$ | $\lambda^{-1} x \in U \}$

is a norm in X.

I prove the first two properties and only the triangular inequality remains. The problem has many parts, so I do not think that all hypotheses are necessary for this part.

I say "infimum norm" but I don't know it's name. If it does have a name, I would be grateful if you could tell me the name.

Best Answer

$\frac 1 {\lambda +\mu} (x+y) =\frac {\lambda} {\lambda +\mu} \frac 1 {\lambda }x+ \frac {\mu} {\lambda +\mu} \frac 1 {\mu }y \in U$ whenever $ \frac 1 {\lambda }x \in U$ and $ \frac 1 {\mu }y \in U$. Can you complete the proof of triangle inequality, given this information?

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