Transformation of lebesgue integral

In summary, the conversation discusses the use of the transformation theorem to obtain the same result as equation (***) by transforming the integral \int f(y)dy into \int f(x^2)2xdx. It is mentioned that X is R, Y is R, and T is sqrt(y). The conversation also mentions the need for a Radon-Nikodym derivative in the solution, which is expressed as \int g(T(x)) d\mu(x) = \int g(y) \frac{d(\mu T^{-1})}{d\mu}(y) \: d\mu(y). The speaker expresses their difficulty in understanding how to use the Radon-Nikodym derivative in this case and
  • #1
grossgermany
53
0
define F(x)=x, then uF is the lebesgue stiljes measure
duF=dx
Let y=x^2
we all know that how to transform [tex]\int f(y)dy [/tex] into [tex]\int f(x^2)2xdx [/tex] (***)
But how exactly would one use the transformation theorem ?
Ie. T be a measurable transformation from X to Y, u is a measure on X
[tex]\int_{Y}fduT^{-1}=\int_{X}fTdu[/tex]

I want to see the transformation theorem in action otherwise it's too abstract for me to understand. My question is, how would one use the transformation theorem to obtain the same result as equation (***)?
 
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  • #2
You should ask yourself the following question: what are X, Y and T in this case?
 
  • #3
X is R
Y is R
T is sqrt(y)
T-1 is y^2

then?
[tex]\int_{Y}fduT^{-1}=\int_{X}fdu y^2 ? [/tex] doesn't make a lot of sense

what is the explicit expression of duT^-1 in this example?
 
  • #4
You need a Radon-Nikodym derivative in there. We have,

[tex]\int g(T(x)) d\mu(x) = \int g(y) \frac{d(\mu T^{-1})}{d\mu}(y) \: d\mu(y).[/tex]
 
  • #5
morphism said:
You need a Radon-Nikodym derivative in there. We have,

[tex]\int g(T(x)) d\mu(x) = \int g(y) \frac{d(\mu T^{-1})}{d\mu}(y) \: d\mu(y).[/tex]

I wonder whether someone could write the next step on the solution of this problem. I must confess that I didn't figure out how to use Radon-Nikodym derivative in this case.

Many thanks
 

1. What is the Lebesgue integral?

The Lebesgue integral is a mathematical concept that is used to calculate the area under a curve. It is based on the Lebesgue measure, which is a way of measuring the size of sets. Unlike the Riemann integral, which is limited to only integrating continuous functions, the Lebesgue integral can integrate a wider class of functions, making it a more powerful tool in mathematical analysis.

2. How does the Lebesgue integral differ from the Riemann integral?

The main difference between the Lebesgue integral and the Riemann integral is the way they partition the interval of integration. The Riemann integral uses a fixed partition, while the Lebesgue integral uses a variable partition, which allows for a more flexible approach to integration. This also allows the Lebesgue integral to integrate a wider class of functions, such as non-continuous and even unbounded functions.

3. What is the motivation behind the transformation of Lebesgue integral?

The transformation of Lebesgue integral is motivated by the need to solve integrals of functions that are not defined on the entire real line. By using a change of variables, the Lebesgue integral can be transformed to integrate over a different domain, making it more convenient to solve certain types of integrals.

4. How does the transformation of Lebesgue integral handle singularities?

The transformation of Lebesgue integral is able to handle singularities, such as discontinuities and points of non-differentiability, by using a partition that avoids these points. This allows for a more accurate and well-behaved integration compared to the Riemann integral, which may have trouble handling these types of functions.

5. What are some practical applications of the transformation of Lebesgue integral?

The transformation of Lebesgue integral has a wide range of applications in mathematics, physics, and engineering. It is commonly used in probability theory, where it allows for the calculation of probabilities for non-continuous random variables. It is also used in signal processing, where it can be used to calculate the Fourier transform of signals that are not defined on the entire real line.

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