Convolutions, Fourier coefficients

Also, if the integrand is not absolutely integrable then more work is needed (e.g. dominated convergence theorem).
  • #1
Incand
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Homework Statement


When ##f## and ##g## are ##2\pi##-periodic Riemann integrable functions define their convolution by
##(f*g)(x) = \frac{1}{2\pi} \int_0^{2\pi} f(y)g(x-y)dy##
Denoting Fourier coefficients by ##c_n(f)## show that ##c_n(f * g) = c_n(f)c_n(g)##.

Homework Equations


##c_n = \frac{1}{2\pi}\int_{-\pi}^{\pi} f(x)e^{-inx}dx##

The Attempt at a Solution


We note that in both ##c_n(f*g)## and ##c_n(f)c_n(g)## get a factor of ##\frac{1}{4\pi^2}## before the integrals so all we have to show is that
##\int_{-\pi}^\pi e^{-inx}\int_0^{2\pi} f(y)g(x-y)dydx = \int_{-\pi}^\pi f(x)e^{-inx}dx \int_{-\pi}^\pi g(y)e^{-iny}dy##
Starting with the left side and changing the order of integration we get
##\int_{-\pi}^\pi e^{-inx}\int_0^{2\pi} f(y)g(x-y)dydx = \int_0^{2\pi} f(y) \int_{-\pi}^\pi g(x-y)e^{-inx}dx.##
Making a change of variables ##z=x-y##
##\int_0^{2\pi} f(y)e^{-iny} \int_{-\pi-y}^{\pi-y} g(z)e^{-inz}dzdy##
which seems somewhat promising except I have the wrong integration interval. Any hints on what I should do to show this? I also tried things like partial integration with derivation under the integral sign but that didn't seem to help me any.
 
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  • #2
First: ##c_{n}(f)\cdot c_{n}(g)=\int_{-\pi}^{\pi}f(u)e^{-inu}du\cdot \int_{-\pi}^{\pi}g(v)e^{-inv}dv=\int_{-\pi}^{\pi}\int_{-\pi}^{\pi}f(u)g(v)e^{-in(u+v)}dudv##. Then let ##v=x-u##:
##c_{n}(f)\cdot c_{n}(g)=\int_{-\pi}^{\pi}\int_{-\pi}^{\pi}f(u)g(v)e^{-in(u+v)}dudv=\int_{-\pi}^{\pi}\int_{-\pi}^{\pi}f(u)g(x-u)e^{-inx}dudx=\int_{-\pi}^{\pi}e^{-inx}(\int_{-\pi}^{\pi}f(u)g(x-u)du)dx##. Some justifications are needed...
 
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  • #3
Svein said:
First: ##c_{n}(f)\cdot c_{n}(g)=\int_{-\pi}^{\pi}f(u)e^{-inu}du\cdot \int_{-\pi}^{\pi}g(v)e^{-inv}dv=\int_{-\pi}^{\pi}\int_{-\pi}^{\pi}f(u)g(v)e^{-in(u+v)}dudv##. Then let ##v=x-u##:
##c_{n}(f)\cdot c_{n}(g)=\int_{-\pi}^{\pi}\int_{-\pi}^{\pi}f(u)g(v)e^{-in(u+v)}dudv=\int_{-\pi}^{\pi}\int_{-\pi}^{\pi}f(u)g(x-u)e^{-inx}dudx=\int_{-\pi}^{\pi}e^{-inx}(\int_{-\pi}^{\pi}f(u)g(x-u)du)dx##. Some justifications are needed...
Thanks for responding! You seem to be doing a similar approach to mine except the other way around. I'm having trouble understanding how you keep the same integration interval when changing variables in the next last step. If you set ##v=x-u##
shouldn't ##x=\pi+u## when ##v=\pi## for example? Perhaps this is one of the justifications I need to discover. I know the change of integration order should be fine since the functions are integrable (i.e. the integrals are convergent).

The other problem is that the convolution integral was defined from ##0\to 2\pi##. Having ##e^{-in\pi} = e^{in\pi}## could possibly help I guess but I don't really get anywhere here either.

Edit: Since ##f## and ##g## is ##2\pi##-periodic perhaps I'm allowed to switch the interval, have to think on this a bit.
 
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  • #4
Incand said:
Since ff and gg is 2π2\pi-periodic perhaps I'm allowed to switch the interval, have to think on this a bit.
Exactly!

The justifications are needed elsewhere.
 
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  • #5
Svein said:
Exactly!

The justifications are needed elsewhere.
I think I get how to change the integration inteval in the last integral now.
The inner integral is
##\int_{-\pi}^\pi f(u)g(x-u)du = \int_{-\pi}^0 f(u)g(x-u)du + \int_0^\pi f(u)g(x-u)du = \int_\pi^{2\pi} f(u)g(x-u)du + \int_0^\pi f(u)g(x-u)du = \int_0^{2\pi} f(u)g(x-u)du## since ##f## and ##g## are two periodic and then so is ##fg##.

And the variable substitution similary
##\int_{-\pi}^\pi f(u) \int_{-\pi}^\pi g(v) e^{-in(u+v)}dvdu = \int_{-\pi}^\pi f(u) \int_{-\pi + u}^{\pi+\pi} g(x-u)e^{-inx}dxdu##
Lets take a closer look at the inner integral
##\int_{-\pi + u}^{\pi+u} g(x-u)e^{-inx}dx = \int_{-\pi}^{\pi} g(x-u)e^{-inx}dx##
since ##f,g## and ##e^{ix}## are all ##2\pi##-periodic. In fact I could've done both these calculations in one step knowing this.
This are all the justifications needed right or is there something else i missed? Thanks for helping!
 
  • #6
Incand said:
This are all the justifications needed right or is there something else i missed?
You need to quote the Fubini theorem when manipulating double integrals. In this case the theorem is trivially satisfied.
 
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Related to Convolutions, Fourier coefficients

What are convolutions?

Convolutions are mathematical operations that combine two functions to produce a third function. They are used to describe how one function affects the other, and are commonly used in signal processing and image filtering.

What is the significance of Fourier coefficients?

Fourier coefficients are used in Fourier analysis to represent a function as a sum of sinusoidal functions with different frequencies and amplitudes. They are important because they allow us to break down complex signals or functions into simpler components, making it easier to analyze and understand them.

What is the difference between discrete and continuous convolutions?

Discrete convolutions are used when the functions involved are only defined at specific points, while continuous convolutions are used for functions that are defined over a continuous range of values. In other words, discrete convolutions are applied to digital signals, while continuous convolutions are used for analog signals.

How are convolutions related to signal filtering?

Convolutions are commonly used in signal filtering to remove unwanted noise or to enhance specific features of a signal. By convolving a signal with a specific filter, we can selectively amplify or attenuate certain frequencies, resulting in a filtered signal with desired characteristics.

What are some real-world applications of convolutions and Fourier coefficients?

Convolutions and Fourier coefficients have numerous applications in fields such as image and audio processing, data compression, and signal analysis. They are also used in machine learning and artificial intelligence for tasks such as image recognition and natural language processing.

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