Convergence in Measure: Difference between revisions

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Let <math>(X, \mathcal{M}, \mu)</math> denote a measure space and let <math>f_n, f : X \to \mathbb{R}</math> for <math>n \in \mathbb{N}</math>. The sequence <math>\{f_n\}_{n \in \mathbb{N}}</math> converges to <math>f</math> in measure if <math>\lim_{n \to \infty} \mu \left( \{x \in X : |f_n(x) - f(x)| \geq \epsilon \} \right) = 0</math> for any <math>\epsilon > 0</math>. Further, the sequence <math> \{f_n\}_{n \in \mathbb{N}} </math> is Cauchy in measure if for every <math> \epsilon > 0, </math> <math> \mu(\{x \in X : |f_n(x) - f_m(x) | \geq \epsilon \}) \to 0 </math> as <math> n,m \to \infty </math> <ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §2.4 </ref>
Let <math>(X, \mathcal{M}, \mu)</math> denote a measure space and let <math>f_n, f : X \to \mathbb{R}</math> for <math>n \in \mathbb{N}</math>. The sequence <math>\{f_n\}_{n \in \mathbb{N}}</math> converges to <math>f</math> in measure if <math>\lim_{n \to \infty} \mu \left( \{x \in X : |f_n(x) - f(x)| \geq \epsilon \} \right) = 0</math> for any <math>\epsilon > 0</math>. Furthermore, the sequence <math> \{f_n\}_{n \in \mathbb{N}} </math> is Cauchy in measure if for every <math> \epsilon > 0, </math> <math> \mu(\{x \in X : |f_n(x) - f_m(x) | \geq \epsilon \}) \to 0 </math> as <math> n,m \to \infty </math> <ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §2.4 </ref>




==Properties==
==Properties==
*If <math> f_n \to f </math> in measure and <math> g_n \to g </math> in measure, then <math> f_n+g_n \to f+g </math> in measure <ref name="Craig1">Katy Craig, ''Math 201a'', Homework 8 </ref>
*If <math> f_n \to f </math> in measure and <math> g_n \to g </math> in measure, then <math> f_n+g_n \to f+g </math> in measure.<ref name="Craig">Craig, Katy. ''MATH 201A HW 8''. UC Santa Barbara, Fall 2020.</ref>
 
*If <math> f_n \to f </math> in measure and <math> g_n \to g </math> in measure, then <math> f_ng_n \to fg </math> in measure if this is a finite measure space. <ref name="Craig">Craig, Katy. ''MATH 201A HW 8''. UC Santa Barbara, Fall 2020.</ref>
*If <math> f_n \to f </math> in measure and <math> g_n \to g </math> in measure, then <math> f_ng_n \to fg </math> in measure <ref name="Craig1"></ref>


==Relation to other types of Convergence==
==Relation to other types of Convergence==
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*If <math> f_n \to f </math> in measure, then there exists a subsequence <math> \{f_{n_k}\}_{k \in \mathbb{N}} </math> such that <math> f_{n_k} \to f </math> almost everywhere.<ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §2.4 </ref>
*If <math> f_n \to f </math> in measure, then there exists a subsequence <math> \{f_{n_k}\}_{k \in \mathbb{N}} </math> such that <math> f_{n_k} \to f </math> almost everywhere.<ref name="Folland">Gerald B. Folland, ''Real Analysis: Modern Techniques and Their Applications, second edition'', §2.4 </ref>


 
*If <math> \mu(X) < \infty </math> and <math> f_n,f </math> measurable s.t. <math> f_n \to f </math> almost everywhere Then <math> f_n \to f </math> in measure.<ref name="Craig, Katy">Craig, Katy. ''MATH 201A Lecture 18''. UC Santa Barbara, Fall 2020.</ref>
 


==References==
==References==

Latest revision as of 07:18, 17 December 2020

Let denote a measure space and let for . The sequence converges to in measure if for any . Furthermore, the sequence is Cauchy in measure if for every as [1]


Properties

  • If in measure and in measure, then in measure.[2]
  • If in measure and in measure, then in measure if this is a finite measure space. [2]

Relation to other types of Convergence

  • If in then in measure [1]
  • If in measure, then there exists a subsequence such that almost everywhere.[1]
  • If and measurable s.t. almost everywhere Then in measure.[3]

References

  1. 1.0 1.1 1.2 Gerald B. Folland, Real Analysis: Modern Techniques and Their Applications, second edition, §2.4
  2. 2.0 2.1 Craig, Katy. MATH 201A HW 8. UC Santa Barbara, Fall 2020.
  3. Craig, Katy. MATH 201A Lecture 18. UC Santa Barbara, Fall 2020.