Vitali convergence theorem
In real analysis and measure theory, the Vitali convergence theorem, named after the Italian mathematician Giuseppe Vitali, is a generalization of the better-known dominated convergence theorem of Henri Lebesgue. It is a characterization of the convergence in in terms of convergence in measure and a condition related to uniform integrability.
Statement of the theorem
Let , with . Then, in if and only if we have
- (i) converge in measure to .
- (ii) For every there exists a measurable set with such that for every disjoint from we have, for every
- (iii) For every there exists such that, if and then, for every we have
Remark: If is finite, then the second condition is trivially true (just pick a subset that covers all but a sufficiently small portion of the whole range). Also, (i) and (iii) implies the uniform integrability of , and the uniform integrability of implies (iii). [1]
Outline of Proof
- For proving statement 1, we use Fatou's lemma:
- Using uniform integrability there exists such that we have for every set with
- By Egorov's theorem, converges uniformly on the set . for a large and . Using triangle inequality,
- Plugging the above bounds on the RHS of Fatou's lemma gives us statement 1.
- For statement 2, use , where and .
- The terms in the RHS are bounded respectively using Statement 1, uniform integrability of and Egorov's theorem for all .
Converse of the theorem
Let be a positive measure space. If
- ,
- and
- exists for every
then is uniformly integrable.[2]
Citations
- SanMartin, Jaime (2016). Teoría de la medida. p. 280.
- Rudin, Walter (1986). Real and Complex Analysis. p. 133. ISBN 978-0-07-054234-1.
gollark: Oh.
gollark: Explain what a "converter" is. I haven't used them.
gollark: What's a converter?
gollark: I agree.
gollark: If it just says you should prove that, then *obviously* you should just differentiate the RHS.
References
- Modern methods in the calculus of variations. 2007. ISBN 9780387357843.
- Folland, Gerald B. (1999). Real analysis. Pure and Applied Mathematics (New York) (Second ed.). New York: John Wiley & Sons Inc. pp. xvi+386. ISBN 0-471-31716-0. MR1681462
- Rosenthal, Jeffrey S. (2006). A first look at rigorous probability theory (Second ed.). Hackensack, NJ: World Scientific Publishing Co. Pte. Ltd. pp. xvi+219. ISBN 978-981-270-371-2. MR2279622
External links
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