Difference between revisions of "Vector space"

(Axioms of a vector space)
Line 13: Line 13:
 
* if <math>x \in V</math>, <math>1.{\mathbf x}={\mathbf x}</math>
 
* if <math>x \in V</math>, <math>1.{\mathbf x}={\mathbf x}</math>
  
===Examples of vector spaces===
+
== Subspaces ==
 +
 
 +
If <math>S \subseteq V</math>, and <math>\mathbf S</math> is a vector space itself, then it is called a subspace of  
 +
<math>\mathbf V</math>.

Revision as of 13:31, 4 November 2006

This article is a stub. Help us out by expanding it.

A vector space over a field (frequently the real numbers) is an object which arises in linear algebra and abstract algebra. A vector space $V$ over a field $F$ consists of a set (of vectors) and two operations, vector addition and scalar multiplication, which obey the following rules:

Axioms of a vector space

  • Scalar multiplication is associative, so if $r, s \in F$ and ${\mathbf v} \in V$ then $(rs){\mathbf v} = r(s{\mathbf v})$.
  • Scalar multiplication is distributive over both vector and scalar addition, so if $r \in F$ and ${\mathbf v, w} \in V$ then $r({\mathbf v + w}) = r{\mathbf v} + r{\mathbf w}$.
  • if $x \in V$, $1.{\mathbf x}={\mathbf x}$

Subspaces

If $S \subseteq V$, and $\mathbf S$ is a vector space itself, then it is called a subspace of $\mathbf V$.