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Where normed vector spaces incorporate the concept of length into a vector space, inner product spaces incorporate the concept of angle.

Definition 1

Let V be a vector space over K . An inner product is a function · , · : V × V K such that for all x , y , z V , α K

  • x , y = y , x ¯
  • α x , y = α x , y
  • x + y , z = x , z + y , z
  • x , x 0 with equality iff x = 0 .

A vector space together with an inner product is called an inner product space .

  • V = C N , x , y : = i = 1 N x i y i ¯ = y * x
  • V = C [ a , b ] , x , y : = a b x ( t ) y ( t ) ¯ d t

Note that a valid inner product space induces a normed vector space with norm x = x , x . (Proof relies on Cauchy-Schwartz inequality.) In R N or C N , the standard inner product induces the 2 -norm. We summarize the relationships between the various spaces introduced over the last few lectures in [link] .

A Venn diagram illustrating the relationships between the various mathematical spaces discussed up to this point.  Metric spaces and vector spaces have a nonzero intersection, and normed vector spaces lie within this intersection.  Inner product spaces lie within the set of normed vector spaces.
Venn diagram illustrating the relationship between vector and metric spaces.

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Source:  OpenStax, Digital signal processing. OpenStax CNX. Dec 16, 2011 Download for free at http://cnx.org/content/col11172/1.4
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