Proof of the convolution theorem

In summary: For x fixed, the integral is over y, but for y fixed, the integral is over x. So for fixed x, dx=0, so we can swap variables as we do not need to worry about the differentials.In summary, when using a variable change to show symmetry in a convolution, we can swap the variables and limits since the dummy variable can be renamed and the differential dx=0 when x is fixed, allowing us to switch the order of integration.
  • #1
albega
75
0

Homework Statement


With the Fourier transform of f(x) defined as F(k)=1/√(2π)∫-∞dxf(x)e-ikx and a convolution of g(x) and h(x) defined by f(x)=[g*h](x)=∫-∞h(x-y)g(y)dy show that the Fourier transform of f(x) equals √(2π)H(k)G(k).

Homework Equations


In problem

The Attempt at a Solution


So I understand the general idea, but I'm stuck on a few little issues. I'm going to drop the integral limits from now on.

F(k)=1/√(2π)∫dx{∫h(x-y)g(y)dy}e-ikx (we can put e-ikx into the integral over y, allowing the next step)

Now the idea is to let z=x-y (we want to get h(z) which will lead us to the form of a Fourier transform for h). However all proofs seems to say this means dx=dz to give

F(k)=1/√(2π)∫dz{∫h(z)g(y)e-ikye-ikzdy}

The question is, why isn't dz=d(x-y)=dx-dy used (given no sources actually discuss this I gather I am being very silly). I also seem

Then
F(k)=√(2π)[1/√(2π)∫h(z)e-ikzdz][1/√(2π)∫g(y)e-ikydy]
=√(2π)H(k)G(k)

If anybody could explain that it would be great, thanks :)
 
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  • #2
albega said:

Homework Statement


With the Fourier transform of f(x) defined as F(k)=1/√(2π)∫-∞dxf(x)e-ikx and a convolution of g(x) and h(x) defined by f(x)=[g*h](x)=∫-∞h(x-y)g(y)dy show that the Fourier transform of f(x) equals √(2π)H(k)G(k).

Homework Equations


In problem

The Attempt at a Solution


So I understand the general idea, but I'm stuck on a few little issues. I'm going to drop the integral limits from now on.

F(k)=1/√(2π)∫dx{∫h(x-y)g(y)dy}e-ikx (we can put e-ikx into the integral over y, allowing the next step)

Now the idea is to let z=x-y (we want to get h(z) which will lead us to the form of a Fourier transform for h). However all proofs seems to say this means dx=dz to give

F(k)=1/√(2π)∫dz{∫h(z)g(y)e-ikye-ikzdy}

The question is, why isn't dz=d(x-y)=dx-dy used (given no sources actually discuss this I gather I am being very silly). I also seem

Then
F(k)=√(2π)[1/√(2π)∫h(z)e-ikzdz][1/√(2π)∫g(y)e-ikydy]
=√(2π)H(k)G(k)

If anybody could explain that it would be great, thanks :)

Use the standard two-dimensional change-of-variable formula from ##(x,y)## to ##(u,v)##, where ##u = y, v = x-y##:
[tex] dx \, dy = \frac{\partial(x,y)}{\partial(u,v)} du \, dv [/tex]
Here, ##\partial(x,y)/\partial(u,v)## denotes the Jacobian of the "transformation" ##x(u,v), \, y(u,v)##.
 
Last edited:
  • #3
Ray Vickson said:
Use the standard two-dimensional change-of-variable formula from ##(x,y)## to ##(u,v)##, where ##u = y, v = x-y##:
[tex] dx \, dy = \frac{\partial(x,y)}{\partial(u,v)} du \, dv [/tex]
Here, ##\partial(x,y)/\partial(u,v)## denotes the Jacobian of the "transformation" ##x(u,v), \, y(u,v)##.

Ahh, silly me, never thought about it as a 2D variable change!

So we have
F(k)=1/√(2π)∫{∫h(x-y)g(y)e-ikxdy}dx

(x,y)->(w,z) where w=y, z=x-y (so that x=w+z, y=w)
Then the Jacobian |∂(x,y)/∂(w,z)|=|(∂x/∂w)(∂y/∂z)-(∂x/∂z)(∂y/∂w)|=|(1)(0)-(1)(1)|=1
Then dxdy=dwdz=dydz and so we're sorted - thanks :)
 
  • #4
Ray Vickson said:
Use the standard two-dimensional change-of-variable formula from ##(x,y)## to ##(u,v)##, where ##u = y, v = x-y##:
[tex] dx \, dy = \frac{\partial(x,y)}{\partial(u,v)} du \, dv [/tex]
Here, ##\partial(x,y)/\partial(u,v)## denotes the Jacobian of the "transformation" ##x(u,v), \, y(u,v)##.

Sorry but I am encountering some trouble with this again:

My notes say that we can show that a convolution
f(x)=∫h(x-y)g(y)dy
is symmetric by writing z=x-y so then (dz=-dy, limits swap)
f(x)=∫h(z)g(x-z)dz
and noting that z is just a dummy variable so we could call it y again if we really wanted so
f(x)=∫h(y)g(x-y)dy.

However how does dy=-dz in the variable change here? We don't have a 2D integral to solve the issue here so I'm confused...

Edit: I gather f(x) is f evaluated at some fixed point x, so that x is fixed and dx=0 here, unlike in the double integral... Correct?
 
Last edited:
  • #5
albega said:
Sorry but I am encountering some trouble with this again:

My notes say that we can show that a convolution
f(x)=∫h(x-y)g(y)dy
is symmetric by writing z=x-y so then (dz=-dy, limits swap)
f(x)=∫h(z)g(x-z)dz
and noting that z is just a dummy variable so we could call it y again if we really wanted so
f(x)=∫h(y)g(x-y)dy.

However how does dy=-dz in the variable change here? We don't have a 2D integral to solve the issue here so I'm confused...

Edit: I gather f(x) is f evaluated at some fixed point x, so that x is fixed and dx=0 here, unlike in the double integral... Correct?

In your first integral, ##y## goes from ##-\infty## to ##+\infty##, while in the second, ##z## goes from ##+\infty## to ##-\infty##. When you re-write that as ##z## going from ##-\infty## to ##+\infty##, your ##-dz## will become a ##+dz##.
 
  • #6
Ray Vickson said:
In your first integral, ##y## goes from ##-\infty## to ##+\infty##, while in the second, ##z## goes from ##+\infty## to ##-\infty##. When you re-write that as ##z## going from ##-\infty## to ##+\infty##, your ##-dz## will become a ##+dz##.
Ray Vickson said:
In your first integral, ##y## goes from ##-\infty## to ##+\infty##, while in the second, ##z## goes from ##+\infty## to ##-\infty##. When you re-write that as ##z## going from ##-\infty## to ##+\infty##, your ##-dz## will become a ##+dz##.

The question was, why is dx zero? But I think I may have answered it myself...
 
  • #7
albega said:
The question was, why is dx zero? But I think I may have answered it myself...

Here was your question: "However how does dy=-dz in the variable change here? We don't have a 2D integral to solve the issue here so I'm confused..."
 
  • #8
Ray Vickson said:
Here was your question: "However how does dy=-dz in the variable change here? We don't have a 2D integral to solve the issue here so I'm confused..."

Sorry I guess it wasn't that clear - but z=x-y, dz=dx-dy, so how does dy=-dz (i.e how is dx=0)...
 
  • #9
albega said:
Sorry I guess it wasn't that clear - but z=x-y, dz=dx-dy, so how does dy=-dz (i.e how is dx=0)...

Have you forgotten that you are trying to equate a product of FTs to the FT of the convolution? That means that you will be integrating over ##x## as well (times ##e^{\pm i kx}##, of course), but that ##x## lies outside the ##y## or ##z## integral, so is like a constant when you are looking at the convolution for fixed ##x##.
 

Related to Proof of the convolution theorem

What is the convolution theorem?

The convolution theorem is a mathematical concept that describes the relationship between the Fourier transforms of two functions and the Fourier transform of their convolution.

How does the convolution theorem work?

The convolution theorem states that the Fourier transform of a convolution of two functions is equal to the product of their individual Fourier transforms. This means that the convolution of two functions in the time domain can be expressed as a simple multiplication in the frequency domain.

Why is the convolution theorem important?

The convolution theorem is an important tool in signal processing, image processing, and other fields of science and engineering. It allows for efficient and accurate calculations of convolutions, which are essential in many applications.

How is the convolution theorem related to the frequency domain and time domain?

The convolution theorem bridges the gap between the time domain and frequency domain. It allows for the analysis of signals in both domains and provides a way to convert between the two representations.

Are there any limitations or assumptions associated with the convolution theorem?

Yes, the convolution theorem assumes that the functions being convolved are continuous and integrable. It also only applies to linear systems and does not work for nonlinear systems. Additionally, the theorem only applies to functions that are defined over the entire real line.

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