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The concept of a '''dual norm''' arises in [[functional analysis]], a branch of mathematics.
 
Let <math>X</math> be a [[normed space]] (or, in a special case, a [[Banach space]]) over a number field <math>{\mathbb F}</math> (i.e. <math>{\mathbb F}={\mathbb C}</math> or <math>{\mathbb F}={\mathbb R}</math>) with [[norm (mathematics)|norm]] <math>\|\cdot\|</math>. Then the [[dual space|''dual'']] (or ''conjugate'') ''normed'' space <math>X'</math> (another notation <math>X^*</math>) is defined as the set of all [[continuous function|continuous]] [[linear functional]]s from <math>X</math> into the base field <math>{\mathbb F}</math>. If <math>f:X\to{\mathbb F}</math> is such a linear functional, then the
''dual norm''<ref>{{harvtxt|A.N.Kolmogorov, S.V.Fomin|1957|loc=III §23}}</ref> <math>\|\cdot\|'</math> of <math>f</math> is defined by
 
: <math> \|f\|'=\sup\{|f(x)|: x\in X, \|x\|\leq 1\}=\sup\left\{\frac{|f(x)|}{\|x\|}: x\in X, x\ne 0\right\}. </math>
 
With this norm, the [[dual space]] <math>X'</math> is also a [[normed space]], and moreover a [[Banach space]], since <math>X'</math> is always complete.
 
<ref>http://www.seas.ucla.edu/~vandenbe/236C/lectures/proxop.pdf</ref>
 
== Examples ==
 
1). '''Dual Norm of Vectors'''
 
If ''p'', ''q'' ∈ <math>[1, \infty]</math> satisfy <math>1/p+1/q=1</math>, then the '''ℓ<sup>p</sup>''' and '''ℓ<sup>q</sup>''' norms are dual to each other. 
 
In particular the [[L2 norm|Euclidean norm]] is self-dual (''p''=''q''=2).  Similarly, the [[Matrix_norm|Schatten ''p''-norm]] on matrices is dual to the Schatten ''q''-norm.
 
For <math>\sqrt{x^TQx}</math>, the dual norm is <math>\sqrt{y^TQ^{-1}y}</math> with <math>Q</math> positive definite.  
 
2). '''Dual Norm of Matrices'''
 
''Frobenius norm''
 
:<math>\|A\|_F=\sqrt{\sum_{i=1}^m\sum_{j=1}^n |a_{ij}|^2}=\sqrt{\operatorname{trace}(A^{{}^*}A)}=\sqrt{\sum_{i=1}^{\min\{m,\,n\}} \sigma_{i}^2}</math>
 
It is dual norm is <math>\|B\|_F</math>
 
''Singular value norm''
:<math>\|A\|_2=\sigma_{max}(A)</math>
Dual norm <math>\sum_i \sigma_i(B)</math>
 
== Notes ==
 
{{reflist}}
 
== References ==
* {{citation
| authorlink = A.N.Kolmogorov; S.V.Fomin
| last1 = Kolmogorov
| first1 = A.N.
| last2 = Fomin
| first2 = S.V.
| year = 1957
| title = Elements of the Theory of Functions and Functional Analysis, Volume 1: Metric and Normed Spaces
| publisher = Graylock Press
| location = Rochester
| isbn =
}}
* {{citation|authorlink=Walter Rudin|first=Walter|last=Rudin|title=Functional analysis|publisher=McGraw-Hill Science|year=1991|isbn=978-0-07-054236-5}}
 
 
[[Category:Linear algebra]]
 
{{mathanalysis-stub}}

Revision as of 16:47, 9 January 2014

The concept of a dual norm arises in functional analysis, a branch of mathematics.

Let X be a normed space (or, in a special case, a Banach space) over a number field 𝔽 (i.e. 𝔽= or 𝔽=) with norm . Then the dual (or conjugate) normed space X (another notation X*) is defined as the set of all continuous linear functionals from X into the base field 𝔽. If f:X𝔽 is such a linear functional, then the dual norm[1] of f is defined by

f=sup{|f(x)|:xX,x1}=sup{|f(x)|x:xX,x0}.

With this norm, the dual space X is also a normed space, and moreover a Banach space, since X is always complete.

[2]

Examples

1). Dual Norm of Vectors

If p, q[1,] satisfy 1/p+1/q=1, then the p and q norms are dual to each other.

In particular the Euclidean norm is self-dual (p=q=2). Similarly, the Schatten p-norm on matrices is dual to the Schatten q-norm.

For xTQx, the dual norm is yTQ1y with Q positive definite.

2). Dual Norm of Matrices

Frobenius norm

AF=i=1mj=1n|aij|2=trace(A*A)=i=1min{m,n}σi2

It is dual norm is BF

Singular value norm

A2=σmax(A)

Dual norm iσi(B)

Notes

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References

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