(New page: Suppose we know the conclusion of problem 8, Problem 8 Let <math>(X,A,mu)</math> be a finite measure space. If f is <math> A </math>measurable, let En = fx 2 X : n 􀀀 1 � jf(x)j < ng:...)
 
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Problem 8
 
Problem 8
Let <math>(X,A,mu)</math> be a finite measure space. If f is <math> A </math>measurable, let
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Let <math>(X,A,m)</math> be a finite measure space. If f is <math> A </math>measurable, let
En = fx 2 X : n 􀀀 1 � jf(x)j < ng:
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<math>E_n = {x \in X : n-1 \leq |f(x)| < n}</math>. Then
Show that f 2 L1 if and only if P1 n=1 n�(En) < 1.
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<math>f \in L^1(X) if and only if sum_{n=1}^{\infty}nm(X) < \inf.</math>
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.<math>(\Rightarrow)</math> First we apply Tchebyshev to <math>E_n</math> and find that
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<math> (n-1)\left|\{x \in X \mid |f(x)| \geq n-1 \}\right| \leq \int_{E_n}|f|</math>
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or rather
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<math>(n-1) m(E_n) \leq \int_{E_n}|f|</math>
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Since we have that <math>m(E_n)</math> is finite we can move it to the other side of the inequality.
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<math>nm(E_n) \leq \int_{E_n}|f| + m(E_n)</math>
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Since this is true for all <math>n</math> we take sums on both sides and note that the <math>E_n</math> are disjoint.
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<math>\sum_{n=1}^{\infty}nm(E_n) \leq \sum_{n=1}^{\infty}\int_{E_n}|f| + \sum_{n=1}^{\infty}m(E_n)</math>
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or
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<math>\sum_{n=1}^{\infty}nm(E_n)\leq \int_{X}|f| + m(X)</math>
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And we are in a finite measure space so <math>m(X) < \infty</math> and since <math>f \in L^1</math> we have <math>\int_{X}|f| < \infty</math>.
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Thus we have that  <math>\sum_{n=1}^{\infty}nm(E_n) < \infty</math>.
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<math>(\Leftarrow)</math> Since <math>|f|< n</math> in each <math>E_n</math> we have that
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<math>\int_X|f| = \sum_{n=1}^{\infty}\left(\int_{E_n}|f|\right) \leq \sum_{n=1}^{\infty}\left( n m(E_n)\right)< \infty</math>
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In other words, <math> f \in L^1</math>.

Revision as of 22:44, 10 July 2008

Suppose we know the conclusion of problem 8,

Problem 8 Let $ (X,A,m) $ be a finite measure space. If f is $ A $measurable, let $ E_n = {x \in X : n-1 \leq |f(x)| < n} $. Then $ f \in L^1(X) if and only if sum_{n=1}^{\infty}nm(X) < \inf. $


.$ (\Rightarrow) $ First we apply Tchebyshev to $ E_n $ and find that

$ (n-1)\left|\{x \in X \mid |f(x)| \geq n-1 \}\right| \leq \int_{E_n}|f| $

or rather

$ (n-1) m(E_n) \leq \int_{E_n}|f| $

Since we have that $ m(E_n) $ is finite we can move it to the other side of the inequality.

$ nm(E_n) \leq \int_{E_n}|f| + m(E_n) $

Since this is true for all $ n $ we take sums on both sides and note that the $ E_n $ are disjoint.

$ \sum_{n=1}^{\infty}nm(E_n) \leq \sum_{n=1}^{\infty}\int_{E_n}|f| + \sum_{n=1}^{\infty}m(E_n) $

or

$ \sum_{n=1}^{\infty}nm(E_n)\leq \int_{X}|f| + m(X) $

And we are in a finite measure space so $ m(X) < \infty $ and since $ f \in L^1 $ we have $ \int_{X}|f| < \infty $.

Thus we have that $ \sum_{n=1}^{\infty}nm(E_n) < \infty $.

$ (\Leftarrow) $ Since $ |f|< n $ in each $ E_n $ we have that

$ \int_X|f| = \sum_{n=1}^{\infty}\left(\int_{E_n}|f|\right) \leq \sum_{n=1}^{\infty}\left( n m(E_n)\right)< \infty $

In other words, $ f \in L^1 $.

Alumni Liaison

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood