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Lebesgue Integration 📂Measure Theory

Lebesgue Integration

Buildup

Before considering the generalization of Riemann integration, it is necessary to define what a simple function is.

Let’s say the range ϕ:RR\phi : \mathbb{R} \to \mathbb{R} of the function values, which are non-negative, is a finite set {a1,a2,,an}\left\{ a_{1} , a_{2}, \cdots , a_{n} \right\}. If it satisfies Ai=ϕ1({ai})MA_{i} = \phi^{-1} \left( \left\{ a_{i} \right\} \right) \in \mathcal{M}, then ϕ\phi is called a simple function. Simple functions have the following properties:

  • (i): If iji \ne j, then AiAj=A_{i } \cap A_{j} = \emptyset
  • (ii): k=1nAk=R\displaystyle \bigsqcup_{k=1}^{n} A_{k} = \mathbb{R}
  • (iii): ϕ(x)=k=1nak1Ak(x)\displaystyle \phi (x) = \sum_{k=1}^{n} a_{k} \mathbb{1}_{A_{k}}(x) is a measurable function.

Simple functions are, by their very definition, composed of three elements that are too easy to handle. Firstly, since the function values are non-negative, there is no need to consider signs; secondly, being finite makes addition and subtraction flexible; and thirdly, they are measurable. The word simple is used in various ways in different fields of mathematics, but at least in real analysis, it can be considered the opposite of ‘complex’. Having defined simple functions that are easy and convenient to handle, it is immediately possible to think of a new integration that covers Riemann integration.

Lebesgue Integration of Simple Functions

When ϕ\phi is a simple function and EME \in \mathcal{M}, Eϕdm:=k=1nakm(AkE)\displaystyle \int_{E} \phi dm := \sum_{k=1}^{n} a_{k} m (A_{k} \cap E) is called the Lebesgue Integral of the simple function ϕ\phi. The Lebesgue integral has the following properties:

  • [1]: For all a>0a>0, Eaϕdm=aEϕdm\displaystyle \int_{E} a \phi dm = a \int_{E} \phi dm
  • [2]: For two simple functions ϕ,ψ\phi , \psi, if ϕψ\phi \le \psi, then EϕdmEψdm\displaystyle \int_{E} \phi dm \le \int_{E} \psi dm
  • [3]: If A,BMA, B \in \mathcal{M} for AB=A \cap B = \emptyset, then ABϕdm=Aϕdm+Bϕdm\displaystyle \int_{A \cup B} \phi dm = \int_{A} \phi dm + \int_{B} \phi dm

However, the condition of being a simple function is too strong and specific to be widely applicable. Adding an idea like the method of exhaustion roughly completes a satisfactory ‘Lebesgue Integral’.

Definition 1

When ϕ\phi is a simple function, for a non-negative measurable function ff and EME \in \mathcal{M}, Efdm:=sup{Eϕdm  0ϕf}\displaystyle \int_{E} f dm := \sup \left\{ \left. \int_{E} \phi dm \ \right| \ 0 \le \phi \le f \right\} is called the Lebesgue Integral of the measurable function ff.

Fundamental Properties

The Lebesgue integral has the following properties:

  • [1]’: For all r0r \ge 0, Erfdm=rEfdm\displaystyle \int_{E} r f dm = r \int_{E} f dm
  • [2]’: For two simple functions f,gf, g, if fgf \le g, then EfdmEgdm\displaystyle \int_{E} f dm \le \int_{E} g dm
  • [3]’: If A,BMA, B \in \mathcal{M} for AB=A \cap B = \emptyset, then ABfdm=Afdm+Bfdm\displaystyle \int_{A \cup B} f dm = \int_{A} f dm + \int_{B} f dm
  • [4]’: If A,BMA, B \in \mathcal{M} for ABA \subset B, then AfdmBfdm\displaystyle \int_{A} f dm \le \int_{B} f dm
  • [5]’: If NNN \in \mathcal{N}, then Nfdm=0\displaystyle \int_{N} f dm = 0
  • [6]’: m(E)infEfEfdmm(E)supEf\displaystyle m(E) \inf_{E} f \le \int_{E} f dm \le m(E) \sup_{E} f

Explanation

In addition to these basic properties, the following theorem can be considered. Using this theorem, calculations as novel as R1Qdm=0\displaystyle \int_{\mathbb{R}} \mathbb{1}_{\mathbb{Q}} dm = 0 can be completed in a single cut. Though not as simple to prove as it appears, it’s certainly worth a look at least once.

Theorem

For measurable functions f0f \ge 0 in a measurable space (X,E)( X , \mathcal{E} ) and all measurable sets AEA \in \mathcal{E}, Afdm=0    f=0 a.e. \int_{A} f dm = 0 \iff f = 0 \text{ a.e.}


Proof

(    )( \implies )

If E:=f1(0,)E := f^{-1} ( 0 , \infty) for m(E)=0m(E) = 0, then ff is almost everywhere f=0f=0. Assuming En:=f1[1n,)\displaystyle E_{n} := f^{-1} \left[ {{1} \over {n}} , \infty \right), if E=n=1En\displaystyle E = \bigcup_{n=1}^{\infty} E_{n} while limnEn=E\displaystyle \lim_{n \to \infty} E_{n} = E holds true. Considering the simple function ϕn:=1n1Enf\displaystyle \phi_{n} := {{1}\over {n}} \mathbb{1}_{E_{n}} \le f, we have 1nm(En)=AϕndmAfdm=0 {{1}\over {n}} m( E_{n} ) = \int_{A} \phi_{n} dm \le \int_{A} f dm = 0 Therefore, 1nm(En)0 {{1} \over {n}} m(E_{n}) \le 0 meaning, for all nNn \in \mathbb{N}, m(En)=0m(E_{n}) = 0.

[7]: EnME_{n} \in \mathcal{M}, EnEn+1    m(n=1En)=limnm(En)\displaystyle E_{n} \subset E_{n+1} \implies m \left( \bigcup_{n=1}^{\infty} E_{n} \right) = \lim_{n \to \infty} m (E_{n})

Meanwhile, since EnEn+1E_{n} \subset E_{n+1}, the following holds true: m(n=1En)=limnm(En)=m(E)=0 m \left( \bigcup_{n=1}^{\infty} E_{n} \right) = \lim_{n \to \infty} m (E_{n}) = m(E) = 0


(    )( \impliedby )

Since ff is almost everywhere f=0f=0 and the simple function ϕ\phi satisfies 0ϕf0 \le \phi \le f, ϕ\phi is also almost everywhere ϕ=0\phi = 0. Thus, Afdm=0\displaystyle \int_{A} f dm = 0 is true.


  1. Capinski. (1999). Measure, Integral and Probability: p77. ↩︎