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Lebesgue Integral

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MeasureTheory

Let (X,F,μ)(X,\mathcal{F},\mu) be a Measure Space, let EFE\in\mathcal{F}. Let f:XR+f:X\to \mathbb{R}^{+} be a Simple Function: f=i=1nai1Aif = \sum_{i=1}^{n}a_{i}\mathbb{1}_{A_{i}} where Ai=f1({αi}), 1inA_{i}=f^{-1}(\{ \alpha_{i} \}),\ \forall_{1}\le i\le n. The Lebesgue Integral of ff with respect to measure μ\mu is defined as: Efdμ=i=1nai μ(AiE)\int\limits _{E}f \, d\mu =\sum_{i=1}^{n}a_{i} \ \mu(A_{i}\cap E)where AiF,ai0A_{i}\in\mathcal{F},a_{i}\ge0.

Let S1,S2S_{1},S_{2} be two simple functions s.t. S1(x)S2(x), xXS_{1}(x)\le S_{2}(x),\ \forall x \in X. Then S1dμS2dμ\int\limits S_{1} \, d\mu\le \int\limits S_{2} \, d\mu

Let f:X[0,)f:X\to[0,\infty) be measurable, (where [0,+]R[0,+\infty]\subset \overline{\mathbb{R}} is equipped with the Induced Topology from the Standard topology). Then \exists increasing sequence (Sn)nN(S_{n})_{n\in\mathbb{N}} of simple functions s.t. f(x)=limnSn(x)f(x)=\lim_{ n \to \infty } S_{n}(x)

We can further the definition of where for f:X[0,)f:X\to[0,\infty) measurable we define the Lebesgue Integral as: Xfdμ=sup{Xgdμ:0g<f, g simple}\int\limits _{X}f \, d\mu =\sup\left\{ \int\limits _{X}g \, d\mu :0\le g<f, \ g \ \text{simple} \right\}

Finally, adding on to the Integral of Positive Measurable Functions, let f:XRf:X\to \mathbb{R} be measurable. Let f+=max(f,0)f^{+}=max(f,0), f=max(f,0)f^{-}=max(-f,0) we define the Lebesgue Integral as: Xfdμ=Xf+dμXfdμ\int\limits _{X}f \, d\mu=\int\limits _{X}f^+ \, d\mu-\int\limits _{X}f^- \, d\mu

Let (X,M,μ)(X,\mathcal{M},\mu) be a Measure Space. Let f,gf,g be measurable functions. Then, 1. Monotonicity: If 0fg0\le f\le g, then EfdμEgdμ\int\limits _{E}f \, d\mu \le\int\limits _{E}g \, d\mu 2. Monotonicity: If ABA\subseteq B, and f0f\ge 0 then, AfdμBfdμ\int\limits _{A}f \, d\mu\le\int\limits _{B}f \, d\mu 3. Linearity: If f0f\ge 0 and cc is a constant, 0c<0\le c<\infty then cfdμ=cfdμc\int\limits f \, d\mu=\int\limits cf \, d\mu 4. If f(x)=0, xEf(x)=0,\ \forall x\in E, then Efdμ=0\int\limits _{E}f \, d\mu=0even if μ(E)=\mu(E)=\infty. 5. If μ(E)=0\mu(E)=0 then Efdμ=0\int\limits _{E}f \, d\mu=0 even if f(x)=f(x)=\infty, xE\forall x \in E. 6. Efdμ=Xf1Edμ\int\limits _{E}f \, d\mu=\int\limits_{X} f\cdot\mathbb{1}_{E} \, d\mu

If f:XCf:X\to \mathbb{C} is s.t. f=u+ivf=u+iv and u,v:XRu,v:X\to \mathbb{R} are measurable functions, and if fL1(X,M,μ)f\in\mathscr{L}^{1}(X,\mathscr{M},\mu) then Efdμ=Eu+dμEudμ+iEv+dμiEvdμ\int\limits _{E}f \, d\mu=\int\limits _{E}u^{+} \, d\mu -\int\limits _{E}u^{-} \, d\mu+i\int\limits_{E}v^{+}\,d\mu-i \int\limits _{E}v^{-} \, d\mu for all EME\in\mathscr{M}. ## Note: f measurable    f+,f measurablef\text{ measurable}\implies f^{+},f^{-}\text{ measurable}by Composition of Measurable Functions. This is only possible with Borel σ-algebra hence why we restrict ourselves to this instead of Lebesgue Measurable. ## Properties 1. Linearity: I(αf+βg)=αI(f)+βI(g)I(\alpha f+\beta g)=\alpha I(f)+\beta I(g) 2. Monotonicity: fg    I(f)I(g)f\le g\implies I(f)\le I(g)

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