The exercise didn't specify anything about $f = \infty$ on sets with positive measure. I'll assume $f$ is a.e. finite. From here, it, of course, suffices to consider only non-negative measurable functions. For any such $f$, we need to find a sequence of continuous functions $\lbrace f_n \rbrace_{n = 1}^{\infty}$ such that the set:
$$E = \Big\lbrace x \in \mathbb{R}^d \hspace{0.25cm} \bigg| \hspace{0.25cm} \lim_{n \to \infty} |f(x) - f_n(x)| > 0 \Big\rbrace$$
has measure zero.
First, define the $d-$dimensional cubes:
$$Q_n = [-n,n]\times \ldots \times[-n,n]$$
And the functions:
$$g_n(x) = \min{\lbrace n,f(x) \rbrace}\chi_{Q_n}$$
It follows from Lusin's Theorem that for any of our $g_n$'s, we can find a set $F_n$ such that $g_n \chi_{F_n}$ is continuous, and $m(Q_n \backslash F_n)\leq \frac{1}{2^{n}}$. Now, we can simply define $f_n = g_n \chi_{F_n}$.
Lastly, define: $E_n = Q_n \backslash F_n$. Notice that:
$$\sum_{n = 1}^{\infty} m(E_n) \leq \sum_{n=1}^{\infty} \frac{1}{2^n} \leq 1$$
Now, of course, we simply need to show that $E$ is $\sup{\lbrace E_n \rbrace}$. This actually isn't all that hard. First, notice:
$$\bigcup_{n \geq k} E_n = \Big\lbrace x \in \mathbb{R}^d \hspace{0.25cm} \bigg| \hspace{0.25cm} |f(x) - f_n(x)| > 0, \hspace{0.25cm} n \geq k \Big\rbrace$$
Naturally, we arrive that the result that $E = \bigcap_{k=1}^{\infty} \bigcup_{n \geq k} E_n$, and thus, by the Borel-Cantelli Lemma, $m(E) = 0$, as desired.
In preparation for a qualifying exam in Real Analysis, during the summer of 2013, I plan to solve as many problems from Stein & Shakarchi's Real Analysis text as I can. Please feel free to comment or correct me as I make my way through this.
Showing posts with label Cantelli. Show all posts
Showing posts with label Cantelli. Show all posts
Friday, May 31, 2013
Thursday, May 30, 2013
1.17
The goal of this exercise is to show that if we choose $c_n$'s as the hint prescribes, the set:
$$E = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} \lim_{n \to \infty} \Big| \frac{f_n(x)}{c_n} \Big| > 0 \Big\rbrace $$
has measure zero. Define:
$$ S_c = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} |f_n(x)| > \frac{c}{n} \Big\rbrace$$
Notice that $m(S_1) \leq 1$. Also, notice $S_{c+1} \subset S_{c} \hspace{0.25cm} \forall c$, and $\bigcap_{c=1}^{\infty}S_c = \emptyset$. Thus, by Corollary 3.3, $\lim_{n \to \infty} m(S_n) = 0$.
With that out of the way, notice that for the sets: $$E_n = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} \Big| \frac{f_n(x)}{c_n} \Big| > \frac{1}{n} \Big\rbrace $$ ...we can choose $c_n$ large enough such that for every $n$, $m(E_n) \leq \frac{1}{2^n}$. Certainly, it follows that ($\dagger$): $$ \sum_{n=1}^{\infty} m(E_n) \leq \sum_{n=1}^{\infty} \frac{1}{2^n} = 1 < \infty $$ Now, observe that $E = \sup{ \lbrace E_n \rbrace }$, i.e. (recalling problem 1.16), $E = \bigcap_{k=1}^{\infty} \bigcup_{n \geq k}E_n$. Thus, applying the Borel-Cantelli Lemma, we have that $$ (\dagger) \Rightarrow m(E) = 0$$
With that out of the way, notice that for the sets: $$E_n = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} \Big| \frac{f_n(x)}{c_n} \Big| > \frac{1}{n} \Big\rbrace $$ ...we can choose $c_n$ large enough such that for every $n$, $m(E_n) \leq \frac{1}{2^n}$. Certainly, it follows that ($\dagger$): $$ \sum_{n=1}^{\infty} m(E_n) \leq \sum_{n=1}^{\infty} \frac{1}{2^n} = 1 < \infty $$ Now, observe that $E = \sup{ \lbrace E_n \rbrace }$, i.e. (recalling problem 1.16), $E = \bigcap_{k=1}^{\infty} \bigcup_{n \geq k}E_n$. Thus, applying the Borel-Cantelli Lemma, we have that $$ (\dagger) \Rightarrow m(E) = 0$$
Wednesday, May 29, 2013
1.16
This exercise is asking us to prove the Borel-Cantelli Lemma. In the measure theory settings, it states:
Since each $E_k \in \mathcal{M}$, certainly $A_n = (\bigcup_{k \geq n} E_k) \in \mathcal{M} \hspace{0.25cm} \forall n$. It follows that since $E = \bigcap_{n=1}^{\infty} A_n$, that $E \in \mathcal{M}$.
Part b.) Assume to the contrary that $m(E) = \delta > 0$. Notice that if we define: $$S_N = \bigcap_{k=1}^N \bigcup_{n \geq k} E_n = \bigcup_{n \geq N} E_n $$ Then, certainly, $S_N \searrow E$, and $\forall N$, $$\delta \leq m(S_N) = m(\bigcup_{n \geq N} E_n) \leq \sum_{n=N}^{\infty} m(E_n)$$ Which certainly contradicts $\dagger$, completing the proof.
Suppose $\lbrace E_n \rbrace_{n=1}^{\infty}$ is a countable family of subsets of $\mathbb{R}^d$, and ($\dagger$) $$\sum_{k=1}^{\infty} m(E_k) < \infty$$ The set $E = \bigcap_{n=1}^{\infty} \bigcup_{k \geq n} E_k$ has measure zero.Part a.) We first need to show $E$ is a measurable set. Recall that the measurable sets form a $\sigma$-algebra, $\mathcal{M}$, which is closed under countable unions and intersections.
Since each $E_k \in \mathcal{M}$, certainly $A_n = (\bigcup_{k \geq n} E_k) \in \mathcal{M} \hspace{0.25cm} \forall n$. It follows that since $E = \bigcap_{n=1}^{\infty} A_n$, that $E \in \mathcal{M}$.
Part b.) Assume to the contrary that $m(E) = \delta > 0$. Notice that if we define: $$S_N = \bigcap_{k=1}^N \bigcup_{n \geq k} E_n = \bigcup_{n \geq N} E_n $$ Then, certainly, $S_N \searrow E$, and $\forall N$, $$\delta \leq m(S_N) = m(\bigcup_{n \geq N} E_n) \leq \sum_{n=N}^{\infty} m(E_n)$$ Which certainly contradicts $\dagger$, completing the proof.
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