L1 Space: Difference between revisions
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===Proof=== | ===Proof=== | ||
<math> 2\implies 1: {\ | <math> 2\implies 1: {\Big\vert}\int_E f-\int_E g{\big\vert}\leq 1_E|f-g|\leq \int |f-g|=0</math> | ||
<math> 3\implies 2: </math> Since <math> f=g</math> a.e., <math>|f-g|=0</math> a.e. Take a simple function, <math> \phi</math>, such that <math> 0\leq \phi\leq |f-g|</math>, such <math>\phi</math> must be <math>0</math> a.e. Therefore, <math> \int |f-g|=\sup\lbrace \int \phi: 0\leq\phi\leq|f-g|,\phi\text{ simple}\rbrace=0</math> | <math> 3\implies 2: </math> Since <math> f=g</math> a.e., <math>|f-g|=0</math> a.e. Take a simple function, <math> \phi</math>, such that <math> 0\leq \phi\leq |f-g|</math>, such <math>\phi</math> must be <math>0</math> a.e. Therefore, <math> \int |f-g|=\sup\lbrace \int \phi: 0\leq\phi\leq|f-g|,\phi\text{ simple}\rbrace=0</math> |
Revision as of 02:12, 18 December 2020
Very much not finished
Introduction
Let be a measure space. From our study of integration, we know that if are integrable functions, the following functions are also integrable:
- , for
This shows that the set of integrable functions on any measurable space is a vector space. Furthermore, integration is a linear functional on this vector space, ie a linear function sending elements in our vector space to , one would like to use integration to define a norm on our vector space. However, if one were to check the axioms for a norm, one finds integration fails to be a norm by taking almost everywhere, then . In other words, there are non zero functions which has a zero integral. This motivates our definition of to be the set of integrable functions up to equivalence to sets of measure zero.
Space
In this section, we will construct .
Definition
Let denote the set of integrable functions on , ie . Define an equivalence relation: if a.e. Then .
To make sense of the definition, we need the following proposition:
Proposition: Let , then the following are equivalent:
- for all
- a.e.
Proof
Since a.e., a.e. Take a simple function, , such that , such must be a.e. Therefore, With the proposition, we define our norm on to be . This is indeed a norm since:
- a.e
Convergence in
With our norm defined, we can the metric to be . With a metric, one can talk about convergence in . This gives us a fourth mode of convergence for a sequence of functions. It is useful to compare these mode of convergence: Uniform Convergence Pointwise Convergence Pointwise a.e. Convergence
However, convergence in does not imply pointwise a.e. convergence and vice versa. To see that, we look at the following examples: