Convolutions, delta functions, etc.

In summary, the dummy variable y represents the variable of integration and the function multiplied by it disappears after the integration is done.
  • #1
reklar
5
0
Okay, these might be better off in two separate threads but...they are somewhat related I suppse.

Anyway, I would like to know how you go about computing the convolution of two functions on the unit circle. Let's say that f(x) = x and g(x) = 1 on the interval [0, Pi] and [0, Pi/2] respectively. I think I get the idea in the discrete case, but seem to have trouble with the continuous case for some reason...

Also, is there a good reference for reading about delta functions, approximate identities and the like? It seems like most texts I've run across barely touch on the subject, but I'd like to see a more thorough, understandable treatment.

Thanks!
 
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  • #2
Do you have an definition of "convolution?"
 
  • #3
Tide said:
Do you have an definition of "convolution?"

Sure,

(f*g)(x) = integral f(x-y)g(y) dy

where the limits of integration are from -Pi to Pi...
 
  • #4
Then all you have to do is apply that definition though the limits of integration will correspond to your particular problem. What, exactly, are you having trouble with?
 
  • #5
Tide said:
Then all you have to do is apply that definition though the limits of integration will correspond to your particular problem. What, exactly, are you having trouble with?

It is a function of x, but what is going on with the y in there?
And the periodic thing throws me a bit I guess...

Anyway, if somone could just do one, perhaps that would make it clearer. I can't seem to find an example in any book I have where this is done...
 
  • #6
"y" is a "dummy variable" that represent the variable of integration so, for example, one of your integrals will look like this:

[tex]\int_{0}^{\pi} (x - y) \times 1 dy[/tex]

for f(x) = x and g(x) = 1. Notice how y no longer appears after performing the integration.
 

1. What is a convolution and how is it used in science?

A convolution is a mathematical operation that combines two functions to produce a third function. In science, convolutions are commonly used to describe the relationship between two physical quantities, such as the input and output of a system. It is also a useful tool for analyzing data and signals.

2. What is a delta function and why is it important?

A delta function, also known as a Dirac delta function, is a mathematical function that is defined as zero everywhere except at one point, where it is infinite. It is important because it can be used to model the behavior of a point-like source or impulse in a system. It is also used in signal processing, where it represents a signal that is concentrated at a single instant in time.

3. How are convolutions and delta functions related?

Convolution and delta functions are closely related in mathematics. The convolution of a function with a delta function results in the original function, while the delta function can be thought of as the derivative of a step function, which is commonly used in convolutions. In science, delta functions are often used as the kernel in convolutions to describe the impulse response of a system.

4. Can convolutions be used in higher dimensions?

Yes, convolutions can be extended to higher dimensions, such as 2D or 3D. In these cases, the operation involves integrating over multiple variables instead of just one. Convolution in higher dimensions is commonly used in image and signal processing, as well as in physics and engineering.

5. Are there any real-world applications of convolutions and delta functions?

Yes, there are many real-world applications of convolutions and delta functions. In physics and engineering, they are used to model and analyze systems, such as in the study of heat transfer. In signal processing, convolutions are used for filtering and smoothing data. They are also used in image processing, such as in edge detection and noise reduction. In addition, delta functions are used in quantum mechanics to describe the behavior of particles at a point in space.

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