How can I easily compute the Fourier Transform of a convolution integral?

In summary, the person is struggling to find a way to compute the Fourier transform of a function, and asks for help. They note that they are almost there, but that they are struggling because they can not apply the convolution theorem. They try using the definition writing \frac{1}{2\pi} \int_{-\infty}^{\infty} \int_{-\infty}^{t} C(t-\tau) \sigma(\tau) \mathrm{d}{\tau} e^{i\omega t} \mathrm{d}t hoping to invertt integration order and
  • #1
muzialis
166
1
Hi there,
I am trying to get some practice with Fourier Transforms, there is a long way to go.
For example, let me consider the function $$ \gamma (t) = \int_{-\infty}^{t} C(t-\tau) \sigma(\tau) \mathrm{d}{\tau}$$
Defining the Fourier Transform as
$$ \gamma(\omega) = \frac{1}{2 \pi} \int_{-\infty}^{\infty} \gamma(t) e^{i\omega t} \mathrm{d}t$$
I am supposed to compute with ease that
$$ \gamma(\omega) = \sigma(\omega) \int_0 ^{\infty} C(t) e^{i\omega t} \mathrm{d}t$$,
but I am struggling, because I can not apply the convolution theorem (as the first equation is a convolution only to actual time).
I tried to use the definition writing
$$\gamma(\omega) = \frac{1}{2\pi} \int_{-\infty}^{\infty} \int_{-\infty}^{t} C(t-\tau) \sigma(\tau) \mathrm{d}{\tau} e^{i\omega t} \mathrm{d}t$$
hoping to invertt integration order and express the inner integral as a Fourier Transform, but again I am not getting anywhere. I tried a variable change $$t-\tau = u$$ and that helps in changing the integration limits to 0 and infinity, but still does not bring me to the desired result, any advice or hint?
Many thanks as usual
 
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  • #2
You are almost there. eiωt = eiω(t-u) eiωu.
After the change of variables and the order of integration switch you have the result, noting that the integral (-∞,∞) is the Fourier transform of σ.

Further suggestion don't use the same symbol for a function and its Fourier transform.
 
  • #3
Mathman,
thanks for your help. I understand your suggestion, I will continue only for this post with the previous notation just not to confuse things further.
I am getting what I would like to, but in a little bit of a shaky way, so I post the calc for a check...
Here is the calculation:

$$\gamma(\omega) = \frac{1}{2\pi} \int_{-\infty}^{\infty} \int_{-\infty}^{t} C(t-\tau) \sigma(\tau) \mathrm{d}{\tau} e^{i\omega t} \mathrm{d}t$$
Using the change of variable $$ t - \tau = u$$ one obtains
$$\gamma(\omega) = \frac{1}{2\pi} \int_{-\infty}^{\infty} \int_{0}^{\infty} C(u) \sigma(t-u) \mathrm{d}{u} \, e^{i\omega (t-u)} e^{i \omega u} \mathrm{d}t$$
inverting the order of integration
$$\gamma(\omega) = \frac{1}{2\pi} \int_{0}^{\infty} \int_{-\infty}^{\infty} C(u) \sigma(t-u) \, e^{i\omega (t-u)} e^{i \omega u} \mathrm{d}t \mathrm{d}{u}$$
and the integrals can be separated now, the one between infinite limits of integration leading the Fourier transform of $\sigma$ (upon a trivial change of variables $$ t - u = z$$ at constant u, is this corrrect?), the final result being as desired
$$\gamma (\omega) = \sigma(\omega) \int_{0}^{\infty} C(u)e^{i\omega u} \mathrm{d}u$$ Many thanks
 
Last edited:
  • #4
It is correct.

(Note - your Latex didn't work in one line).
 
  • #5
Mathman, many thanks much appreciated.
 

1. What is the Fourier Transform?

The Fourier Transform is a mathematical tool used to analyze the frequency components of a signal. It decomposes a signal into its constituent sine and cosine waves, which can then be further analyzed and manipulated.

2. How is the Fourier Transform used in science?

The Fourier Transform is used in various fields of science, such as physics, engineering, and signal processing. It is used to analyze and filter signals, image processing, and solving differential equations, among other applications.

3. What is the difference between the continuous and discrete Fourier Transform?

The continuous Fourier Transform is used for signals that are continuous and infinite, while the discrete Fourier Transform is used for signals that are discrete and finite. The discrete Fourier Transform is often used in practical applications as it can be easily calculated using computers.

4. What is the inverse Fourier Transform?

The inverse Fourier Transform is the mathematical operation that takes the frequency components of a signal and reconstructs the original signal. It is the opposite of the Fourier Transform and is used to convert a signal from the frequency domain back to the time domain.

5. What are some limitations of the Fourier Transform?

The Fourier Transform assumes that the signal is stationary, meaning that it does not change over time. It also assumes that the signal is periodic, meaning that it repeats itself infinitely. These assumptions may not hold true for all signals, leading to limitations in the accuracy of the Fourier Transform.

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