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Clearly, one may define a norm on C ( [ a, b ], R n ) to make it a normed vector space.
We define a norm, the so-called Luxemburg norm, on this space by the formula (1.4).
Now, we define a norm in E by |x|_{omega}=sup_{tgeq0}big| e^{omega t}S t)xbig|.
Although does not define a norm in, it holds that the defines a metric on, and makes into a complete metric space.
Further we define a norm on C Q m by ∥ x ∥ C Q m = max k ∥ x ∥ C m ( J k ).
Let (A=C_{1}^{R}[0,1]) and define a norm on A by (Vert xVert = Vert xVert _{infty} + Vert x^{prime} Vert _{infty}) for (xin A).
Similar(42)
We show that if Xt is a continuous martingale with X0 = 0 then the quantity supt E Xtlog(Mt+Mt−)) defines a norm on H1 martingales equivalent to the usual norm.
We note that the expression defines a norm on.
If is a Young function, then defines a norm in, which is called the Luxemburg norm.
It is easy to show that (|cdot|_{X_{T}}) defines a norm on (X_{T}).
It is easy to verify that (3) defines a norm on (f(bar{N})).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com