Definition of Integral in Multiple Variables

In summary, the dyadic cube relation between two cubes is such that the supremum of a function on one cube is the minimum value of the function on the other cube.
  • #1
Astrum
269
5
Dyadic Cube [tex]C_{k,N} = X \in\ \mathbb{R}^{n} \frac{k_{i}}{2^{N}} \leq x_{i} < \frac{k_{i}+1}{2^{N}} for 1 \leq i \leq n[/tex]

Where [tex]k = \pmatrix {
k_{1} \cr
k_{2} \cr
\vdots \cr
k_{i} \cr
} [/tex]

I understand that N is the level of the cubes, but what does k equal?

I'm having trouble visualizing this in my head.

[itex]A \subset \mathbb{R}^{n}[/itex]

[tex] M_{A}(f)= supp_{x \in A}f(x); m_{A}(f) = inf_{x \in A}f(x)[/tex] [tex] U_{N}(f) = \sum M_{c}(f) vol_{n}C [/tex] [tex] L_{N}(f) = \sum m_{c}(f) vol_{n}C [/tex]

I get the general idea, but I can't really see this in my head.

If you take the supp value of a function on a given cube, and multiply it by the volume of you cube, you get volume again??

I can't really get the image straight.

I get that this is just an extension of single variable, so it means that U must equal L which must equal I (integral).
 
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  • #2
Astrum said:
Dyadic Cube [tex]C_{k,N} = X \in\ \mathbb{R}^{n} \frac{k_{i}}{2^{N}} \leq x_{i} < \frac{k_{i}+1}{2^{N}} for 1 \leq i \leq n[/tex]

Where [tex]k = \pmatrix {
k_{1} \cr
k_{2} \cr
\vdots \cr
k_{i} \cr
} [/tex]

I understand that N is the level of the cubes, but what does k equal?

[...]

If you take the supp value of a function on a given cube, and multiply it by the volume of you cube, you get volume again??
Let's see if we can work this out.

What does k do in your dyadic cube relation? What does it act on?

As for your second question, what is the supremum of a function in this case?

I think the answers are in asking those questions. :wink:
 
  • #3
Well, from what I understand, the supf(x) is the maximum value of the function on a given cube, which in single variable gives a height to the rectangle. In multiple dimensions, I can't "see" it. I assume that this also gives.

As for what k means, I guess it means the number of cubes under the graph?

I can't find any other sources explaining this, perhaps my book just has a weird way of defining the multiple integral.
 

What is the definition of an integral in multiple variables?

The integral in multiple variables is a mathematical concept that represents the accumulation of a quantity over a region in multiple dimensions. It is used to calculate the total value of a function over a given region in space.

What is the difference between a single variable integral and a multiple variable integral?

A single variable integral involves integrating a function over a one-dimensional interval, while a multiple variable integral involves integrating a function over a region in multiple dimensions. This means that a multiple variable integral takes into account the variation of a function in more than one direction.

How is the integral in multiple variables calculated?

The integral in multiple variables is calculated using a process called integration, which involves summing up infinitesimal elements of a region to determine the total value of a function over that region. This process can be done using various techniques, such as double or triple integration, depending on the number of variables involved.

What is the significance of the integral in multiple variables in real-world applications?

The integral in multiple variables is an important tool in many fields of science and engineering, as it allows for the calculation of physical quantities such as volume, mass, and energy over a given region in space. It is also used in calculus to solve optimization problems and to determine the average value of a function over a region.

What are some common applications of the integral in multiple variables?

The integral in multiple variables is used in a wide range of applications, including physics, engineering, economics, and statistics. It is used to calculate the center of mass, moment of inertia, and work done in physics, as well as to solve optimization problems in economics and statistics. It is also used in computer graphics to render three-dimensional images and in fluid mechanics to calculate fluid flow.

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