Vector measure

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In mathematics, a vector measure is a function defined on a family of sets and taking vector values satisfying certain properties.

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[edit] Definitions and first consequences

Given a field of sets (\Omega, \mathcal F) and a Banach space X, a finitely additive vector measure (or measure, for short) is a function \mu:\mathcal {F} \to X such that for any two disjoint sets A and B in \mathcal{F} one has

\mu(A\cup B) =\mu(A) + \mu (B).

A vector measure μ is called countably additive if for any sequence (A_i)_{i=1, 2, \dots} of disjoint sets in \mathcal F such that their union is in \mathcal F it holds that

\mu\left(\displaystyle\bigcup_{i=1}^\infty A_i\right) =\sum_{i=1}^{\infty}\mu(A_i)

with the series on the right-hand side convergent in the norm of the Banach space X.

It can be proved that an additive vector measure μ is countably additive if and only if for any sequence (A_i)_{i=1, 2, \dots} as above one has

\lim_{n\to\infty}\left\|\mu\left(\displaystyle\bigcup_{i=n}^\infty A_i\right)\right\|=0, \quad\quad\quad (*)

where \|\cdot\| is the norm on X.

Countably additive vector measures defined on sigma-algebras are more general than measures, signed measures, and complex measures, which are countably additive functions taking values respectively on the extended interval [0, \infty], the set of real numbers, and the set of complex numbers.

[edit] Examples

Consider the field of sets made up of the interval [0,1] together with the family \mathcal F of all Lebesgue measurable sets contained in this interval. For any such set A, define

\mu(A)=\chi_A\,

where χ is the indicator function of A. Depending on where μ is declared to take values, we get two different outcomes.

  • μ, viewed as a function from \mathcal F to the Lp space L^\infty([0, 1]), is a vector measure which is not countably-additive.
  • μ, viewed as a function from \mathcal F to the Lp space L1([0,1]), is a countably-additive vector measure.

Both of these statements follow quite easily from the criterion (*) stated above.

[edit] The variation of a vector measure

Given a vector measure \mu:\mathcal{F}\to X, the variation | μ | of μ is defined as

|\mu|(A)=\sup \sum_{i=1}^n \|\mu(A_i)\|

where the supremum is taken over all the partitions

A=\bigcup_{i=1}^n A_i

of A into a finite number of disjoint sets, for all A in \mathcal{F}. Here, \|\cdot\| is the norm on X.

The variation of μ is a finitely additive function taking values in [0, \infty]. It holds that

||\mu(A)||\le |\mu|(A)

for any A in \mathcal{F}. If | μ | (Ω) is finite, the measure μ is said to be of bounded variation. One can prove that if μ is a vector measure of bounded variation, then μ is countably additive if and only if | μ | is countably additive.

[edit] References

  • Diestel, J.; Uhl, Jr., J. J. (1977). Vector measures. Providence, R.I: American Mathematical Society. ISBN 0821815156. 
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