Saturday, 24 May 2014

real analysis - Essential Uniform Convergence Implication



Greetings Mathematics Community. I believe that I am thinking too hard about the following problem and would like some guidance in solving it.



Let X have finite measure and let fn:XC and f:XC be measurable functions. Show that if fn converges to f in Lnorm, then fn also converges to f in L1norm.



The definitions that I am working with are as follows:



We say that fn converges to f uniformly almost everywhere, essentially uniformly, or in Lnorm if, for every ϵ>0, there exists N such that for every nN,|fn(x)f(x)|ϵ for μalmost every xX. The Lnorm ||f||L(μ) of a measurable function f:XC is defined to be the infimum of all the quantities M[0,+] that are essential upper bounds for f in the sense that |f(x)|M for almost every x. Then fn converges to f in L norm if and only if ||fnf||L(μ)0 as n.




We say that fn converges to f in L1norm if the quantity ||fnf||L1(μ)=X|fn(x)f(x)|dμ converges to 0 as n.



Here is my attempt at solving this problem:



Since fn converges to f in L norm, then we have
||fn(x)f(x)||0 as n and by definition, ||fn(x)f(x)||=inf. Then ||f_n(x)-f(x)||_1 = \int |f_n(x)-f(x)|dx.



Here is where I am stuck: Could I create another function g such that ||g(x)||_1 \leq ||g(x)||_{\infty} and somehow include Markov's Inequality to show that the L^1 norm converges?



Alternatively, could I simply say that \int|f_n(x)-f(x)|dx \leq ||f_n(x)-f(x)||_{\infty} and since we are given that f_n converges to f in L^{\infty}norm, then \int|f_n(x)-f(x)|dx \leq 0?




I would be grateful for any advice or guidance. Thanks in advance.


Answer



\|f_n-f\|_1=\int_X|f_n-f|d\mu\le\|f_n-f\|_{\infty}\mu(X).


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