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| <strong> Egerov's Theorem </strong>:Suppose <math> \mu </math> is a locally finite Borel measure and <math>\{f_n\}</math> is a sequence of measurable functions defined on a measurable set <math> E </math> with <math> \mu(E)<\infty </math> and <math> f_n \rightarrow f </math> a.e. on E. | | <strong> Egerov's Theorem </strong>: Suppose <math> \mu </math> is a locally finite Borel measure and <math>\{f_n\}</math> is a sequence of measurable functions defined on a measurable set <math> E </math> with <math> \mu(E)<\infty </math> and <math> f_n \rightarrow f </math> a.e. on E. |
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Revision as of 21:06, 7 December 2020
Statement
Egerov's Theorem : Suppose is a locally finite Borel measure and is a sequence of measurable functions defined on a measurable set with and a.e. on E.
Then:
Given we may find a closed subset such that and uniformly on [1]
Proof
WLOG assume for all since the set of points at which is a null set. Fix and for we define
. Since are measurable so is their difference. Then since the absolute value of a measurable function is measurable each is measurable.
Now for fixed we have that and . Therefore using continuity from below we may find a such that .
Now choose so that and define . By countable subadditivity we have that .
Fix any . We choose such that . Since if then . And by definition if then whenever . Hence uniformly on .
Finally, since is measurable, using HW5 problem 6 there exists a closed set such that . Therefore and on
Corollary
Bounded Convergence Theorem : Let be a seqeunce of measurable functions bounded by , supported on a set and a.e. Then
[2]
Proof
By assumptions on , is measurable, bounded, supported on for a.e. x. Fix , then by Egerov we may find a measurable subset of such that and uniformly on . Therefore, for sufficiently large we have that for all . Putting this together yields
Since was arbitrary and is finite by assumption we are done.
References
- ↑ Stein & Shakarchi, Real Analysis: Measure Theory, Integration, and Hilbert Spaces, Chapter 1 §4.3
- ↑ Stein & Shakarchi, Real Analysis: Measure Theory, Integration, and Hilbert Spaces, Chapter 2 § 1