Fourier Transform and Parseval's Theorem

In summary: The Fourier transform of ##f(t)g(t)## is defined as:$$\int^\infty_{-\infty} f(t)g(t) e^{-2 \pi \nu t} dt$$
  • #1
roam
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Homework Statement


Using Parseval's theorem,

$$\int^\infty_{-\infty} h(\tau) r(\tau) d\tau = \int^\infty_{-\infty} H(s)R(-s) ds$$

and the properties of the Fourier transform, show that the Fourier transform of ##f(t)g(t)## is

$$\int^\infty_{-\infty} F(s)G(\nu-s)ds$$

Homework Equations


Fourier transform for ##f(t)g(t)## is defined as:

$$\int^\infty_{-\infty} f(t)g(t) e^{-2 \pi \nu t} dt$$

The Attempt at a Solution


So starting from the definition of Fourier transform:

$$\int^\infty_{-\infty} f(t)g(t) e^{-2 \pi \nu t} dt$$

So, do we need to ignore the exponential term here? If we ignore it, we can apply Parseval's theorem to get the frequency domain:

$$\int^\infty_{-\infty} f(t)g(t) dt = \int^\infty_{-\infty} F(s) G(- s) d s$$

Now, what property of the Fourier transform can I use to get ##G(-s) \implies G(\nu-s)##?

I don't understand what the ##(\nu-s)## part means, does it indicates some sort of shifting or delay in the input? :confused:

Any help is greatly appreciated.
 
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  • #2
I think you forgot an ##i## in the exponent in the definition of Fourier transform.

You cannot just ignore the exponential term in ##\int^\infty_{-\infty} f(t)g(t) e^{-2 \pi iv t} dt##

Start with ##G(v-s)## for a fixed ##v##.
Write out the formula for ##G(v-s)##, and you will note that ##G(v-s)=\mathcal F (g_v(-s))## for some function ##g_v## (##\mathcal F## denotes the Fourier transform).

Using that knowledge about ##G(v-s)##, apply Parseval's theorem to ##\int^\infty_{-\infty} F(s)G(v-s)ds## and see what you get ...

A little remark about terminology:
roam said:
show that the Fourier transform of ##f(t)g(t)## is

$$\int^\infty_{-\infty} F(s)G(\nu-s)ds$$
It is clearer when you write something like:
the Fourier transform of ##f(t)g(t)## in ##\nu## is $$\int^\infty_{-\infty} F(s)G(\nu-s)ds$$
 
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  • #3
Thank you for your input. In ##g_v## what does the subscript ##v## mean? Should it not be ##g_t## since ##G(s)## is the Fourier transform of ##g(t)##? (In my course a function denoted by a capital letter is the Fourier transform of the function denoted by the corresponding small letter)

So from the definition, the formula for the ##G(v-s)## part is:

$$G(v-s) = \int^\infty_{-\infty} g(t) e^{-i 2 \pi st} dt$$

Here I used the duality property of the Fourier transform i.e. ##F(t) \iff f(-s)##

Is this the right formula?
 
  • #4
roam said:
Thank you for your input. In ##g_v## what does the subscript ##v## mean? Should it not be ##g_t## since ##G(s)## is the Fourier transform of ##g(t)##? (In my course a function denoted by a capital letter is the Fourier transform of the function denoted by the corresponding small letter)

So from the definition, the formula for the ##G(v-s)## part is:

$$G(v-s) = \int^\infty_{-\infty} g(t) e^{-i 2 \pi st} dt$$

Here I used the duality property of the Fourier transform i.e. ##F(t) \iff f(-s)##

Is this the right formula?
There is no ##v## in your right hand side expression for ##G(v-s)##, so that can't be correct.

I really meant ##g_v##. Just pick one ##v## as a constant and let's work with that for a while.

In general, the definition of the Fourier transform is:
$$G(u) = \int^\infty_{-\infty} g(t) e^{-2 \pi iut} dt$$

I deliberately used another name for the variable here.
Now set ##u=v-s## in that definition. You get:
$$G(v-s) = \int^\infty_{-\infty} g(t) e^{-2 \pi i(v-s)t} dt=\int^\infty_{-\infty} \Big(g(t)e^{- 2 \pi ivt}\Big)e^{-2 \pi i(-s)t} dt$$

Compare that last expression with the definition of the Fourier transform. What we have there is the Fourier transform of the function between the big brackets at the point ##-s##. So now name the function between the big brackets ##g_v##, and what we have is that:
$$g_v(t)=g(t)e^{-2 \pi ivt}$$
$$G(v-s)=\mathcal F(g_v(-s))$$
Or, if you prefer the convention of your course:
$$G(v-s)=G_v(-s)$$
Now apply this to evaluate ##\int^\infty_{-\infty} F(s)G(v-s)ds##, by using Parseval's theorem.
 
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  • #5
Never mind. I thought something was wrong, but I was wrong about that.

My sincere apologies for my confusion.
 
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  • #6
I see. Thank you very much for the clear explanation.

$$\int^\infty_{-\infty} F(s) G(\nu -s) ds = \int^\infty_{-\infty} F(s) G_\nu (-s) ds$$

using Parseval's theorem this becomes:

$$\int^\infty_{-\infty} f(t) g_\nu (t) dt = \int^\infty_{-\infty} f(t) g(t) e^{-2 \pi i \nu t} dt$$

Is this then sufficient to 'show' that ##\int^\infty_{-\infty} F(s) G(\nu -s)ds## is the Fourier transform of ##f(t)g(t)##?
 
  • #7
roam said:
I see. Thank you very much for the clear explanation.

$$\int^\infty_{-\infty} F(s) G(\nu -s) ds = \int^\infty_{-\infty} F(s) G_\nu (-s) ds$$

using Parseval's theorem this becomes:

$$\int^\infty_{-\infty} f(t) g_\nu (t) dt = \int^\infty_{-\infty} f(t) g(t) e^{-2 \pi i \nu t} dt$$

Is this then sufficient to 'show' that ##\int^\infty_{-\infty} F(s) G(\nu -s)ds## is the Fourier transform of ##f(t)g(t)##?
Yes, because taking the two equations together, you now proved that for any ##\nu##: $$ \int^\infty_{-\infty} f(t) g(t) e^{-2 \pi i \nu t}=\int^\infty_{-\infty} F(s) G(\nu -s) ds$$
The left hand side is by definition the Fourier transform of the function ##f.g## at point ##\nu##.

As an aside, ##\int^\infty_{-\infty} F(s) G(\nu -s) ds## is called the convolution of F and G at ##\nu##. (More here and here)
 
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  • #8
Thank you so much for your help. That was very helpful.
 

Related to Fourier Transform and Parseval's Theorem

1. What is the Fourier Transform?

The Fourier Transform is a mathematical operation that decomposes a function into its constituent frequencies, allowing us to analyze complex signals and systems in terms of simpler sinusoidal functions.

2. How is the Fourier Transform calculated?

The Fourier Transform is typically calculated using an integral, which involves multiplying the function by a complex exponential and integrating over the entire domain of the function. This results in a new function that represents the amplitudes and phases of each frequency component of the original function.

3. What is Parseval's Theorem and how is it related to Fourier Transform?

Parseval's Theorem is a mathematical statement that relates the energy of a function in the time domain to its energy in the frequency domain. It states that the integral of the squared magnitude of a function in the time domain is equal to the integral of the squared magnitude of its Fourier Transform.

4. What are some applications of Fourier Transform and Parseval's Theorem?

The Fourier Transform and Parseval's Theorem have a wide range of applications in various fields such as signal processing, image processing, data compression, and differential equations. They are also used in physics, engineering, and finance for analysis and modeling of various systems and phenomena.

5. Are there any limitations to using Fourier Transform and Parseval's Theorem?

While the Fourier Transform and Parseval's Theorem are powerful tools for analyzing signals and systems, there are some limitations to their use. These include the assumption of linearity and time-invariance, as well as the need for continuous and periodic signals. Additionally, the Fourier Transform may not be suitable for signals with discontinuities or sharp edges.

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