Monotone Convergence Theorem: Difference between revisions
ChienHsunLin (talk | contribs) (Created page with "==Monotone Convergence Theorem== ===Theorem=== Suppose <math>\{f_n\}</math> is a sequence of non-negative measurable functions, <math> f_n: X \to [0,+\infty]</math> such that...") |
mNo edit summary |
||
(11 intermediate revisions by 3 users not shown) | |||
Line 1: | Line 1: | ||
== | ==Theorem== | ||
Consider the measure space <math> (X,\mathcal{M},\mu) </math> and suppose <math>\{f_n\}</math> is a sequence of non-negative measurable functions, <math> f_n: X \to [0,+\infty]</math> such that <math> f_{n} \leq f_{n+1} </math> for all <math>n \in \mathbb{N}</math>. | |||
Furthermore, <math> \lim_{n\to+\infty} f_n = f ( = \sup_n f_n) </math>. | Furthermore, <math> \lim_{n\to+\infty} f_n = f ( = \sup_n f_n) </math>. | ||
Then | Then | ||
:<math> \lim_{n\to+\infty} \int f_n = \int \lim_{n\to+\infty} f_n .<ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §2.2 </ref></math> | :<math> \lim_{n\to+\infty} \int f_n = \int \lim_{n\to+\infty} f_n .</math><ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §2.2 </ref> | ||
==Proof== | |||
First we prove that <math> \lim_{n\rightarrow +\infty} \int f_n \leq \int \lim_{n\rightarrow +\infty} f_n </math>. | |||
Since <math> f_{n} \leq f_{n+1} </math> for all <math>n \in \mathbb{N}</math>, we have <math> f_n\leq \lim_{n\rightarrow +\infty} f_n </math> and further <math> \int f_n\leq \int \lim_{n\rightarrow +\infty} f_n </math>. | |||
Sending <math>n\rightarrow +\infty</math> on LHS gives us the result. | |||
Then we only need to prove that <math> \lim_{n\rightarrow +\infty} \int f_n \geq \int \lim_{n\rightarrow +\infty} f_n </math>. In this regard, denote <math> | |||
g = \lim_{n\rightarrow +\infty} f_n </math> (which is measurable as the limit of measurable functions) and consider a simple function <math> \phi </math> so that <math> 0 \leq \phi \leq g </math>. | |||
Now, for <math> n \in \mathbb{N} </math> and some <math> t \in (0,1) </math>, define the increasing sequence of measurable sets <math> E_n = \{x \in X \mid f_n - t\cdot\phi > 0\} </math>. Since <math> f_n\leq f_{n+1} </math>, we have <math> E_n \subseteq E_{n+1} </math> for <math> n \in \mathbb{N} </math>. Moreover, we have <math> X = \cup_{n=1}^{\infty} E_n </math> since <math> g = \sup_{n\in \mathbb{N}} f_n </math>. | |||
Recall that the set function <math> \nu(A) = \int_{A} \phi \, d\mu</math> for <math> A \in \mathcal{M} </math> is a measure on <math> (X,\mathcal{M},\mu) </math>. We now see that <math> \lim_{n\rightarrow +\infty} \int_{X} f_n \geq \lim_{n\rightarrow +\infty} \int_{E_n} f_n \geq t \cdot \lim_{n\rightarrow +\infty} \int_{E_n} \phi = t \cdot \int_{X} \phi </math>, where we have used the fact that <math> \nu(X) = \nu(\cup_{n=1}^{\infty} E_n) = \lim_{n\rightarrow +\infty} \nu(E_n) </math> for the last equality. Taking the supremum over simple functions such that <math> 0 \leq \phi \leq g </math> and the supremum over <math> t \in (0,1) </math> yields the required inequality. | |||
==References== | ==References== |
Latest revision as of 20:27, 8 December 2020
Theorem
Consider the measure space and suppose is a sequence of non-negative measurable functions, such that for all . Furthermore, . Then
Proof
First we prove that .
Since for all , we have and further .
Sending on LHS gives us the result.
Then we only need to prove that . In this regard, denote (which is measurable as the limit of measurable functions) and consider a simple function so that .
Now, for and some , define the increasing sequence of measurable sets . Since , we have for . Moreover, we have since .
Recall that the set function for is a measure on . We now see that , where we have used the fact that for the last equality. Taking the supremum over simple functions such that and the supremum over yields the required inequality.
References
- ↑ Gerald B. Folland, Real Analysis: Modern Techniques and Their Applications, second edition, §2.2