Content deleted Content added
Fgnievinski (talk | contribs) |
|||
(3 intermediate revisions by 3 users not shown) | |||
Line 1:
{{Short description|Length in a vector space}}
{{About|
In [[mathematics]], a '''norm''' is a [[function (mathematics)|function]] from a real or complex [[vector space]] to the non-negative real numbers that behaves in certain ways like the distance from the [[Origin (mathematics)|origin]]: it [[Equivariant map|commutes]] with scaling, obeys a form of the [[triangle inequality]], and is zero only at the origin. In particular, the [[Euclidean distance]] in
A [[seminorm]] satisfies the first two properties of a norm, but may be zero for vectors other than the origin.<ref name="Knapp">{{cite book|title=Basic Real Analysis|publisher=Birkhäuser|author=Knapp, A.W.|year=2005|page=[https://books.google.com/books?id=4ZZCAAAAQBAJ&pg=279] |isbn=978-0-817-63250-2}}</ref> A vector space with a specified norm is called a [[normed vector space]]. In a similar manner, a vector space with a seminorm is called a ''seminormed vector space''.
Line 45 ⟶ 46:
The [[absolute value]]
<math
is a norm on the
Any norm <math>p</math> on a one-dimensional vector space <math>X</math> is equivalent (up to scaling) to the absolute value norm, meaning that there is a norm-preserving [[isomorphism]] of vector spaces <math>f : \mathbb{F} \to X,</math> where <math>\mathbb{F}</math> is either <math>\R</math> or <math>\Complex,</math> and norm-preserving means that <math>|x| = p(f(x)).</math>
|