Real Analysis: L∞(E) Norm as Limit of a Sequence

SqueeSpleen
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Real Analysis, L∞(E) Norm as the limit of a sequence.

|| f ||_{\infty} is the lesser real number M such that | \{ x \in E / |f(x)| > M \} | = 0 (| \cdot | used with sets is the Lebesgue measure).

Definition:
For every 1 \leq p < \infty and for every E such that 0 < | E | < \infty we define:
N_{p} [f] = (\frac{1}{ | E | } \displaystyle \int_{E} | f |^{p})^{\frac{1}{p}}

a) p_{1} < p_{2} \Rightarrow N_{p_{1}} [f] \leq N_{p_{2}} [f]
b) N_{p} [f+g] \leq N_{p} [f] + N_{p} [g]
c) If \frac{1}{p} + \frac{1}{q} = 1 \frac{1}{ | E | } \displaystyle \int_{E} | f g | \leq N_{p} [f] N_{q} [g]
d) \lim_{p \to \infty} N_{p} [f] = | | f | |_{\infty}

I need help with the a), I couldn't solve it. I didn't got anything good in my attemps, so I'll show my work in the other three points (Also I'm taking the opportunity to someone find any mistake I could have overlooked).

b) By triangular inequality of the norm || \cdot ||_{p} and observing that:
| E |^{\frac{1}{p}} N_{p} = || \cdot ||_{p}
We have:
| E |^{\frac{1}{p}} N_{p} [f+g] \leq | E |^{\frac{1}{p}} N_{p} [f] + | E |^{\frac{1}{p}} N_{p} [g]
Divide both sides by | E |^{\frac{1}{p}} the work is done.c) By Hölder Inequality we have: \displaystyle \int_{E} | f g | \leq (\int_{E} | f |^{p} )^{\frac{1}{p}}(\int_{E} | g |^{q})^{\frac{1}{q}}
We divide both sides by | E | and knowing that as \frac{1}{p}+\frac{1}{q}=1 we have:
\frac{1}{| E |} \displaystyle \int_{E} | f g | \leq \frac{1}{| E |} (\int_{E} | f |^{p} )^{\frac{1}{p}}(\int_{E} | g |^{q})^{\frac{1}{q}} = (\frac{1}{| E |} \int_{E} | f |^{p} )^{\frac{1}{p}}(\frac{1}{| E |} \int_{E} | g |^{q})^{\frac{1}{q}}d) Let be the sequence of nonnegative simple functions \{ \varphi_{n} \}_{n \in \mathbb{N}} with \varphi_{n} \leq \varphi_{n+1} \forall n \in \mathbb{N} and:
\lim_{n \to \infty} \varphi_{n} = | f |.
It's clear that \lim_{n \to \infty} \varphi_{n} = | f | if and only if \lim_{n \to \infty} \varphi_{n}^{p} = | f |^{p} as:
\phi_{n} = \displaystyle \sum_{i=1}^{m_{n}} \alpha_{i,n} X_{E_{i,n}} \Longrightarrow \phi_{n}^{p} = \displaystyle \sum_{i=1}^{m_{n}} \alpha_{i,n}^{p} X_{E_{i,n}}
Let be \varphi a non negative simple function such that:
\varphi \leq | f |

\varphi = \displaystyle \sum_{i=1}^{m} \alpha_{i} X_{E_{i}} with | E_{i} | > 0 \forall i: 1 \leq i \leq m and:
\alpha_{1} < \alpha_{2} < ... < \alpha_{m}
\displaystyle \int_{E} \varphi^{p} = \displaystyle \sum_{i=1}^{m} \alpha_{i}^{p} | E_{i} |
As p \to \infty \alpha_{m}^{p} | E_{m} | grows faster than \displaystyle \sum_{i=1}^{m} \alpha_{i}^{p} | E_{i} |, to every \varepsilon > 0 \exists p \in \mathbb{R} such that:
| \frac{\displaystyle \sum_{i=1}^{m} \alpha_{i}^{p} | E_{i} |}{\alpha_{m}^{p} | E_{m} |} -1 | < \varepsilon
As all coefficients of the sumatory are positive, we can drop the absolute value bars.
\frac{\displaystyle \sum_{i=1}^{m} \alpha_{i}^{p} | E_{i} |}{\alpha_{m}^{p} | E_{m} |} -1 < \varepsilon
Then
\displaystyle \sum_{i=1}^{m} \alpha_{i}^{p} | E_{i} | < (1+\varepsilon) \alpha_{m}^{p} | E_{m} |
Then we have:
\alpha_{m}^{p} | E_{m} | \leq \int_{E} \varphi^{p} < (1 + \varepsilon) \alpha_{m}^{p} | E_{m} |
We divide by | E | sides and take power to \frac{1}{p} and we have:
((1 + \varepsilon) \frac{E_{m}}{| E |})^{1/p} \alpha_{m}
As p \to \infty this converges to \alpha_{m}
Now by Beppo-Levi we have:
\lim_{n \to \infty} \int_{E} \varphi_{n}^p = \int_{E} |f|^{p}
(We are using the simple functions \varphi_{n}^p to aproximate | f |^{p}
We power both sides to \frac{1}{p} and we are almost done.
The only thing left it to prove that || f ||_{\infty} = \lim_{n \to \infty} (\lim_{p \to \infty} N_{p} [ \varphi_{n} ]) which is easy, because to every set with positive measure, taking n big enough we'll have a \varphi_{n} with that set, then the norm infinity is the supremum of that sequence, and as this is an increasing sequence then it's the limit.
 
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part a. See the following (the norm he defines here is the ##L_p## norm):

Moreover, if we're on a bounded domain, we also have the relatively standard result that if f∈Lp1 for some p1∈[1,∞), then it is in Lp for every p≤p1 (which can be shown using Hölder's inequality). http://math.stackexchange.com/quest...ble-for-a-function-to-be-in-lp-for-only-one-pThis is more general.
Let M be the set of all measures of subsets of your space. Then, if p<q, then Lp < Lq if M has a positive lower bound, and Lq < Lp if M has a finite upper bound. http://www.johndcook.com/blog/2012/11/11/how-lp-spaces-nest/
 
Thanks, tomorrow I'll ask my teacher about this problem.
 
Isn't the L^{p}(E) norm:
| | f | | = (\displaystyle \int_{E} | f |^{p} )^{\frac{1}{p}}
?
This one is different, it has the measure of E dividing before the root.
 
You are right, the E is inside the root, which I didn't quite see. Well, I found you a proof. The finite measure of E is necessary, and shown by the counterexample at the bottom. The division by |E| falls out of his final inequality.

http://math.stackexchange.com/questions/66029/lp-and-lq-space-inclusion

Theorem Let X be a finite measure space. Then, for any 1≤p<q≤+∞
Lq(X,B,m)⊂Lp(X,B,m).
The proof follows from Hölder inequality. Note that 1/p=1/q+1/r, with r>0. Hence
∥f∥Lp≤meas (X)1/r∥f∥Lq.

The case reported on the wikipedia link of commenter answer follows from this, since of course, if X does not contain sets of arbitrary large measure, X itself can't have an arbitrary large measure.

For the counterexample: f(x)=1/x belongs to L2([1,+∞)), but clearly it does not belong to L1([1,+∞)).

Has your prof discussed measure in detail?
 
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What do you mean by "discussed measure in detail"? (I wouldn't know, I have not any reference course to compare).
I think we did, our first set of practices were enterely of Lebesgue measure and we spend roughly 1/3 of the course (5-6 weeks) doing it.
Later we had a brief views about "abstract measures"

Elemental sets -> \sigma - elemental sets -> Borelians and a couple of ways of generate them.
External lebesgue measure.
Lebesgue Measure
Internal lebesgue measure, non-measurable sets.

That was more or less what we covered on measure before we moved to measurable functions.

We saw that for sets of finite measure L^{p}(E) \subset L^{q}(E) if q \leq p
For infinite measure I know it's false because I already had the oportunity to solve the following exercise:
Let be E = [0,\infty).
Prove that f(x) = x^{\frac{1}{2}} (1+|ln(x)|)^{-1} \in L^{2} (E) but f \notin L^{p} (E) \forall p \in [0,\infty) - \{ 2 \}
 
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I'll transcribe here what I understood from the links.
| E | &lt; \infty
Let be p,q / 1 \leq p \leq q \Longrightarrow 1 &lt; \frac{q}{p}
Then there exists s \in \mathbb{R} such that:
1 = \frac{p}{q} + \frac{1}{s}
There exists a r \in \mathbb{R} such that s= \frac{r}{p}
1 = \frac{p}{q} + \frac{p}{r}
Now we apply the Hölder inequality:
\displaystyle \int_{E} | f |^{p} = \displaystyle \int_{E} | f |^{p} \cdot X_{E} \leq | E |^{\frac{p}{r}} ( \displaystyle \int_{E} (| f |^{p})^{\frac{q}{p}} )^{\frac{p}{q}} = | E |^{\frac{p}{r}} ( \displaystyle \int_{E} | f |^{q} )^{\frac{p}{q}}
We power to \frac{1}{p}:
( \displaystyle \int_{E} | f |^{p})^{\frac{1}{p}} \leq | E |^{\frac{1}{r}} ( \displaystyle \int_{E} | f |^{q} )^{\frac{1}{q}}
\frac{1}{r} = \frac{1}{p} - \frac{1}{q} \Longrightarrow | E |^{\frac{1}{r}} = \frac{| E |^{\frac{1}{p}}}{| E |^{\frac{1}{q}}}
\frac{1}{| E |^{\frac{1}{p}}} ( \displaystyle \int_{E} | f |^{p})^{\frac{1}{p}} \leq \frac{1}{| E |^{\frac{1}{q}}} ( \displaystyle \int_{E} | f |^{q} )^{\frac{1}{q}}
\therefore ( \frac{1}{| E |} \displaystyle \int_{E} | f |^{p})^{\frac{1}{p}} \leq ( \frac{1}{| E |}\displaystyle \int_{E} | f |^{q} )^{\frac{1}{q}}

 
It sounds like you did indeed cover a lot of measure theory -- certainly more than I ever did. I never took a course in it specifically; covered Lp spaces in a course either on real or functional analysis. So maybe you should be helping me?

It looks to me like your interpretation of the sketchy proof I sent you is correct.

I don't think you need the line about s. If p/q < 1 then there has to be a real number that fills in the gap, and p/r is as good as any (since r can be whatever works). This doesn't invalidate your proof in any way. It's just a little roundabout and where you can simplify that kind of thing it's a good idea.
 
The course is of real analysis, both we spend a lot of time in the first chapter.

And I found that you can directly apply the following generalization of Hölder inequality:
\displaystyle \sum_{i=1}^{m} p_{i} = \frac{1}{r} \wedge f_{i} \in L^{p_{i}} \forall i : 1 \leq i \leq m \Longrightarrow || \displaystyle \prod_{i=1}^{m} f_{i} ||_{r} \leq \displaystyle \prod_{i=1}^{m} | | f_{i} | |_{p_{i}}

Thank you very much for your help again, I think this is the hardest course I ever toke and I really need help (As I don't speak English very well I really feel I need to say it explicity because I may sound a little rude to people helping me but it's only because my English is quite basic).
 
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SqueeSpleen said:
The course is of real analysis, both we spend a lot of time in the first chapter.

And I found that you can directly apply the following generalization of Hölder inequality:
\displaystyle \sum_{i=1}^{m} p_{i} = \frac{1}{r} \wedge f_{i} \in L^{p_{i}} \forall i : 1 \leq i \leq m \Longrightarrow || \displaystyle \prod_{i=1}^{m} f_{i} ||_{r} \leq \displaystyle \prod_{i=1}^{m} | | f_{i} | |_{p_{i}}

Thank you very much for your help again, I think this is the hardest course I ever toke and I really need help (As I don't speak English very well I really feel I need to say it explicity because I may sound a little rude to people helping me but it's only because my English is quite basic).

I wish my real analysis course had spent more time on measures. You have not sounded rude to me, but it is nice to get thanked. I really enjoy helping with problems, and I learn a lot too.
 

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