Where Does the Convolution Theorem Come From?

In summary,The equation 9 in the article states that the convolution of two signals with different time delays is given by the following equation:X_1(f) * X_2(f) e^{-j 2 \pi f t_i}
  • #1
bugatti79
794
1
Hi Folks,

I have an article which explains the modulation of 2 signals given by

[tex]X_1(f) e^{-j 2 \pi f t_i}[/tex] and [tex]X_2(f) e^{-j 2 \pi f t_i}[/tex]

The only difference between the 2 signals is a time delay, however i don't see a phase difference in either expression

It states the convolution of these 2 signals in the frequency domain is given as

[tex]X_1 (f) * X_2(f) e^{-j 2 \pi f t_i}[/tex]

Where does this come from? I expected something of the form, from basic rules,

[tex]A e^{iat} B e^{iat}= A B e^{i2at}[/tex]
 
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  • #2
bugatti79 said:
Hi Folks,

I have an article which explains the modulation of 2 signals given by

[tex]X_1(f) e^{-j 2 \pi f t_i}[/tex] and [tex]X_2(f) e^{-j 2 \pi f t_i}[/tex]

The only difference between the 2 signals is a time delay, however i don't see a phase difference in either expression

It states the convolution of these 2 signals in the frequency domain is given as

[tex]X_1 (f) * X_2(f) e^{-j 2 \pi f t_i}[/tex]

Where does this come from? I expected something of the form, from basic rules,

[tex]A e^{iat} B e^{iat}= A B e^{i2at}[/tex]

Hi bugatti79!

It looks to me as if your formulas are somewhat incomplete.

It looks like $X_1(f)$ is the frequency spectrum of the first signal.
If I assume that to be true, then the corresponding signal would be:
$$x_1(t_i) = \int_0^\infty X_1(f)e^{-j 2 \pi f t_i} df$$
So it seems as if the integral was left out.The convolution (from Fourier theory) of $x_1(t_i)$ and $x_2(t_i)$ would be:
$$x_1(t_i) * x_2(t_i) = \mathscr{F}^{-1}(X_1(f)\cdot X_2(f)) = \int_0^\infty X_1(f)\cdot X_2(f)e^{-j 2 \pi f t_i} df$$
 
  • #3
I like Serena said:
Hi bugatti79!

It looks to me as if your formulas are somewhat incomplete.

It looks like $X_1(f)$ is the frequency spectrum of the first signal.
If I assume that to be true, then the corresponding signal would be:
$$x_1(t_i) = \int_0^\infty X_1(f)e^{-j 2 \pi f t_i} df$$
So it seems as if the integral was left out.The convolution (from Fourier theory) of $x_1(t_i)$ and $x_2(t_i)$ would be:
$$x_1(t_i) * x_2(t_i) = \mathscr{F}^{-1}(X_1(f)\cdot X_2(f)) = \int_0^\infty X_1(f)\cdot X_2(f)e^{-j 2 \pi f t_i} df$$
Hi there!,

Thanks for the reply. The paper doesn't seem to evaluate the integral... i have attached the extract for your convenience. Its just one page. I am puzzled how he arrived at eqn 9...
 

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  • #4
bugatti79 said:
Hi there!,

Thanks for the reply. The paper doesn't seem to evaluate the integral... i have attached the extract for your convenience. Its just one page. I am puzzled how he arrived at eqn 9...

Ah okay.

Suppose $\mathscr F(x_1(t)) = X_1(f)$.
And suppose $x_i(t)$ is the same signal shifted in time by $t_i$.
So $x_i(t) = x_1(t-t_i)$.

Then:
\begin{aligned}X_i(f) &= \int_{-\infty}^\infty x_i(t)e^{-j2\pi f t}dt \\
&=\int_{-\infty}^\infty x_1(t-t_i)e^{-j2\pi f t}dt \\
&=e^{-j2\pi f t_i}\int_{-\infty}^\infty x_1(t-t_i)e^{-j2\pi f (t-t_i)}d(t-t_i)\\
&=e^{-j2\pi f t_i}\int_{-\infty}^\infty x_1(\tau)e^{-j2\pi f \tau}d\tau \\
&=X_1(f)e^{-j2\pi f t_i}
\end{aligned}

Or in short:
$$X_i(f) = X_1(f) e^{-j2\pi f t}$$
That is, a shift in time in the signal $x_1(t)$ results in a factor $e^{-j2\pi f t}$ in the frequency spectrum.
 
  • #5
I like Serena said:
Ah okay.

Suppose $\mathscr F(x_1(t)) = X_1(f)$.
And suppose $x_i(t)$ is the same signal shifted in time by $t_i$.
So $x_i(t) = x_1(t-t_i)$.

Then:
\begin{aligned}X_i(f) &= \int_{-\infty}^\infty x_i(t)e^{-j2\pi f t}dt \\
&=\int_{-\infty}^\infty x_1(t-t_i)e^{-j2\pi f t}dt \\
&=e^{-j2\pi f t_i}\int_{-\infty}^\infty x_1(t-t_i)e^{-j2\pi f (t-t_i)}d(t-t_i)\\
&=e^{-j2\pi f t_i}\int_{-\infty}^\infty x_1(\tau)e^{-j2\pi f \tau}d\tau \\
&=X_1(f)e^{-j2\pi f t_i}
\end{aligned}

Or in short:
$$X_i(f) = X_1(f) e^{-j2\pi f t}$$
That is, a shift in time in the signal $x_1(t)$ results in a factor $e^{-j2\pi f t}$ in the frequency spectrum.

Hi,

That is clear to me now however, the equation before (9), I am not sure how the exp term was handled. It seems only one of the exp terms was brought forward instead of the 2 exp terms...ie it seems

[tex]A e^{iat} B e^{iat}= A B e^{iat}[/tex]

I was expecting it to be

[tex]A e^{iat} B e^{iat}= A B e^{2iat}[/tex]...?
 
  • #6
bugatti79 said:
Hi,

That is clear to me now however, the equation before (9), I am not sure how the exp term was handled. It seems only one of the exp terms was brought forward instead of the 2 exp terms...ie it seems

[tex]A e^{iat} B e^{iat}= A B e^{iat}[/tex]

I was expecting it to be

[tex]A e^{iat} B e^{iat}= A B e^{2iat}[/tex]...?

That's a nice conundrum! ;)

But it is correct, since:
$$
\left(X(f)e^{-j2\pi ft_i}\right) * \left(Y(f)e^{-j2\pi ft_i}\right)
=\mathscr F\Big(x(t-t_i) \cdot y(t-t_i)\Big)
=\mathscr F\Big((x \cdot y)(t-t_i)\Big)
=\Big(X(f) * Y(f)\Big) e^{-j2\pi ft_i}
$$
 
  • #7
bugatti79 said:
Hi,

That is clear to me now however, the equation before (9), I am not sure how the exp term was handled. It seems only one of the exp terms was brought forward instead of the 2 exp terms...ie it seems

[tex]A e^{iat} B e^{iat}= A B e^{iat}[/tex]
I was expecting it to be

[tex]A e^{iat} B e^{iat}= A B e^{2iat}[/tex]...?

Hi,

Sorry if i seem ignorant on the matter, but how do you mean a conundrum?
 
  • #8
bugatti79 said:
Hi,

Sorry if i seem ignorant on the matter, but how do you mean a conundrum?

I mean that it's a nice puzzle showing an unexpected property of convolution.

What you expected would be correct if we'd be talking about multiplication. But we're not - it is about convolution. which behaves subtly different, as I've shown in my previous post.
 
  • #9
I like Serena said:
I mean that it's a nice puzzle showing an unexpected property of convolution.

What you expected would be correct if we'd be talking about multiplication. But we're not - it is about convolution. which behaves subtly different, as I've shown in my previous post.

Ah...now i see the light! Thank you!

I like Serena said:
=e^{-j2\pi f t_i}\int_{-\infty}^\infty x_1(t-t_i)e^{-j2\pi f (t-t_i)}d(t-t_i)

Can you point to an online source that shows this kind of integration...ie d(x-y)

[tex]\int f(x) d(x-y)[/tex]

Thanks
 
  • #10
I like Serena said:
That's a nice conundrum! ;)

But it is correct, since:
$$
\left(X(f)e^{-j2\pi ft_i}\right) * \left(Y(f)e^{-j2\pi ft_i}\right)
=\mathscr F\Big(x(t-t_i) \cdot y(t-t_i)\Big)
=\mathscr F\Big((x \cdot y)(t-t_i)\Big)
=\Big(X(f) * Y(f)\Big) e^{-j2\pi ft_i}
$$

Ok, i guess you have used something along the fact that [tex] \frac{1}{\sqrt{2 \pi}} F(w)*G(w)= \mathscr F[(ft) g(t)[[/tex]...?

Can we use the convolution theorem itself $$(f*g)(w)=\int_{0}^w f(\tau) g(w-\tau) d\tau$$

to show
[tex]\left(X(f)e^{-j2\pi ft_i}\right) * \left(Y(f)e^{-j2\pi ft_i}\right)=\Big(X(f) * Y(f)\Big) e^{-j2\pi ft_i} [/tex]...?

Thanks
 
  • #11
bugatti79 said:
Ok, i guess you have used something along the fact that [tex] \frac{1}{\sqrt{2 \pi}} F(w)*G(w)= \mathscr F[(ft) g(t)[[/tex]...?

Yes, but without the constant factor.
It's the Convolution Theorem, which you can find on wiki.

Can we use the convolution theorem itself $$(f*g)(w)=\int_{0}^w f(\tau) g(w-\tau) d\tau$$

to show

[tex]\left(X(f)e^{-j2\pi ft_i}\right) * \left(Y(f)e^{-j2\pi ft_i}\right)=\Big(X(f) * Y(f)\Big) e^{-j2\pi ft_i} [/tex]...?

I was using the "convolution theorem". Presumably you meant the "definition of convolution", but what you're asking is to prove that the convolution theorem is true.
You can find that proof on the wiki page I've just mentioned.
 
  • #12
I like Serena said:
Yes, but without the constant factor.
It's the Convolution Theorem, which you can find on wiki.
I was using the "convolution theorem". Presumably you meant the "definition of convolution", but what you're asking is to prove that the convolution theorem is true.
You can find that proof on the wiki page I've just mentioned.

Great, thanks!
 

FAQ: Where Does the Convolution Theorem Come From?

What is a noise signal in frequency domain?

A noise signal in frequency domain is a type of signal that contains random variations in amplitude and phase across different frequencies. It is often characterized by a flat power spectrum, meaning that the signal has equal power across all frequencies.

What causes a noise signal in frequency domain?

A noise signal in frequency domain can be caused by various factors, such as interference from other electronic devices, thermal noise from electrical circuits, or random fluctuations in a system's output.

How is a noise signal in frequency domain measured?

A noise signal in frequency domain can be measured using a spectrum analyzer, which displays the signal's power spectrum. The amplitude of the signal at each frequency can be measured to determine the signal's noise level.

What are the effects of a noise signal in frequency domain?

The effects of a noise signal in frequency domain can include reduced signal quality and accuracy, interference with other signals, and difficulty in extracting useful information from the signal. It can also impact the performance of electronic systems and devices.

How can a noise signal in frequency domain be reduced?

A noise signal in frequency domain can be reduced by using techniques such as filtering, shielding, and grounding to eliminate or reduce the sources of noise. Additionally, signal processing techniques can be used to remove noise from the signal.

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