How Does the DC Component Affect the Fourier Transform of a Signal?

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Discussion Overview

The discussion revolves around the impact of the DC component on the Fourier Transform of a signal, specifically analyzing the system response to a given transfer function and input signal. Participants explore the mathematical implications of the DC component in the context of Fourier analysis, including the transformation of constant terms and sinusoidal inputs.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant considers the system response to a transfer function H(w) = 10/(jw + 10) with an input x(t) = 2 + 2*cos(50*t + pi/2), questioning how to handle the DC component '2' in the Fourier Transform.
  • Another participant suggests staying in the Fourier domain and expresses that X(w) should include both the DC component and the Fourier transform of the cosine term.
  • There is a proposal to use the relationship cos(x + π/2) = -sin(x) to simplify the cosine term in the analysis.
  • Some participants discuss the inverse transform process and the implications of using the delta function in the Fourier Transform, particularly how it relates to the system response.
  • There is confusion about the correct application of the delta function and its role in the Fourier Transform, with one participant expressing difficulty in understanding its application.
  • One participant attempts to clarify the integration process for the inverse transform and the significance of evaluating the integral at specific points, particularly at w = 0 for the DC component.
  • Another participant raises a question about the Fourier series of a series of delta functions, seeking clarification on the interpretation and integration of such a series.

Areas of Agreement / Disagreement

Participants exhibit a mix of agreement and disagreement, particularly regarding the treatment of the DC component and the application of the Fourier Transform. Some participants agree on the need to consider both the DC and AC components, while others express uncertainty about the correct mathematical approach and the implications of the delta function.

Contextual Notes

There are limitations in the discussion regarding the assumptions made about the delta function and the Fourier Transform. Some participants express confusion about the integration process and the correct application of the Fourier series, indicating a need for further clarification on these concepts.

Who May Find This Useful

This discussion may be useful for students and practitioners in electrical engineering, signal processing, and applied mathematics who are exploring the Fourier Transform and its applications to signals with DC components.

  • #31
toneboy1 said:
Since I've just been up all night here, when I stumbled across sin(w) and I was trying to inverse Fourier transform it, I thought I'd done it before, it should be "elementary!", but now looking at it I tried and found myself integrating (from Euler's Identity):
1/2pi * [(exp(2jwt)-1)/2j] ∞→-∞

which obviously doesn't work or trying to use Duality on the table with no success in getting the: j√(pi/2)*[del(t+1)-del(t-1)] that wolfram generated as the answer.

Anyway, a question for another time perhaps.

Thanks for your assistance!

Look at the link I sent you. It tells you how F{sin(wt)} is derived. They use the time-displaced delta function in the w domain in a clever way.

I don't know what field you hope to go into, but if it's electrical engineering I would de-emphasize the Fourier transform and concentrate on the LaPlace. The Fourier comes into its own in optics and statistical control system design (for which the two-sided LaPlace is equally suitable).
 
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  • #32
rude man said:
BTW I like the following site for the Fourier transform:

http://www.thefouriertransform.com/transform/fourier.php

rude man said:
Look at the link I sent you. It tells you how F{sin(wt)} is derived. They use the time-displaced delta function in the w domain in a clever way.

I don't know what field you hope to go into, but if it's electrical engineering I would de-emphasize the Fourier transform and concentrate on the LaPlace. The Fourier comes into its own in optics and statistical control system design (for which the two-sided LaPlace is equally suitable).

Right'o, I will concentrate on LaPlace because I am in Electrical Eng; I have done more LaPlace a couple of years ago, than I ever have Fourier.

In that link you sent me, I assume the Sinc and the Sin in which you refer are one and the same. I did notice that using l'hospital's rule sinc(0) = 1 for division by 0 which makes sense.

[ On what might be a side note: I'm confused because my Transform table says (using κ for tau) Pof width κ(t) is transformed to κSinc(κω/2pi) but in examples I can see Pκ(t) is transformed into (2/ω)*sin(κω/2) Which would mean that Pκ(t) is transformed into κSinc(κω/2), so where has the pi in the denominator gone? ]To be clear, we're talking about sin(w) FROM frequency domain to time domain aren't we?
(I was trying to use Duality to multiply Sin(w) by 2.pi to get the: j√(pi/2)*[δ(t+1)-δ(t-1)]
Wolfram generated.)

Cheers
 
  • #33
toneboy1 said:
Right'o, To be clear, we're talking about sin(w) FROM frequency domain to time domain aren't we?
(I was trying to use Duality to multiply Sin(w) by 2.pi to get the: j√(pi/2)*[δ(t+1)-δ(t-1)]
Wolfram generated.)

Cheers

I goofed again. I was thinking F{sin(wt)}, not F-1{sin(w)}. Sorry.

But the technique is similar: think the time-delayed delta function.
 
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  • #34
toneboy1 said:
Right'o, [ On what might be a side note: I'm confused because my Transform table says (using κ for tau) Pof width κ(t) is transformed to κSinc(κω/2pi) but in examples I can see Pκ(t) is transformed into (2/ω)*sin(κω/2) Which would mean that Pκ(t) is transformed into κSinc(κω/2), so where has the pi in the denominator gone? ]

The Fourier transform of a pulse of height 1 and width 2T is F(w) = (T/π)(sin(wT)/wT.
Some folks call sin(x)/x = sinc(x) but I've also seen different definitions of sinc so I avoid that designation in general.

As an aside: you can't let T → ∞ to derive F(1). You have to invoke the delta function.
 
  • #35
rude man said:
The Fourier transform of a pulse of height 1 and width 2T is F(w) = (T/π)(sin(wT)/wT.
Some folks call sin(x)/x = sinc(x) but I've also seen different definitions of sinc so I avoid that designation in general.

Just experimenting, I noticed if w = 3, width = 2 then
(2/w)*sin(2*w/2) is ALMOST the same as (2.pi/w)*sin(2*w/2.pi),
so you seem right about it being a notational thing, but what I can't understand is that the one with the pi in it seems more accurate because in one instance the number was finite and the other kept going. Can you see why this would be?

rude man said:
I goofed again. I was thinking F{sin(wt)}, not F-1{sin(w)}. Sorry.

But the technique is similar: think the time-delayed delta function.
H'mm, I'm still not clear, I'll elaborate on where I got stuck:

x(t) = (1/2pi)* ∫ (exp(jwt)-exp(-jwt) /2j)*exp(jwt) dw -∞ to ∞

∴ (1/2pi)* ∫(exp(2jwt)-exp(0) / 2j) dw -∞ to ∞

∴ (1/j4pi)*[exp(2jwt)/2jw - w ] -∞ to ∞

And I'm not sure where to go from here. (especially with your time delay)

Alternatively using duality and linearity I attempted to make

sin(ω) = 2pi*sin(-w)/2pi

inverse transformed into: j.pi/2pi * [δ(1-t)-δ(t-1)] which is wrong according to wolfram.

Cheers for any input!
 
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  • #36
toneboy1 said:
Just experimenting, I noticed if w = 3, width = 2 then
(2/w)*sin(2*w/2) is ALMOST the same as (2.pi/w)*sin(2*w/2.pi),
so you seem right about it being a notational thing, but what I can't understand is that the one with the pi in it seems more accurate because in one instance the number was finite and the other kept going. Can you see why this would be?

Not sure what you're getting at here.

In the below, where on Earth did you get that equation? You're apparently trying to do an inverse transform on sin(wt)?? On a function containing t ?

H'mm, I'm still not clear, I'll elaborate on where I got stuck:

x(t) = (1/2pi)* ∫ (exp(jwt)-exp(-jwt) /2j)*exp(jwt) dw -∞ to ∞

Cheers for any input!

I think I need to go to bed! :rolleyes:
Cheers!
 
  • #37
rude man said:
Not sure what you're getting at here.

In the below, where on Earth did you get that equation? You're apparently trying to do an inverse transform on sin(wt)?? On a function containing t ?



I think I need to go to bed! :rolleyes:
Cheers!

[I was saying
(2/w)*sin(2*w/2) ≈ (2.pi/w)*sin(2*w/2.pi)
for reasons I cannot reckon]

Woops, good call, it should have been 't'less, I.e:
x(t) = (1/2pi)* ∫ (exp(jw)-exp(-jw) /2j)*exp(jwt) dw -∞ to ∞


Heh, heh, fairenough, Night.
 
  • #38
toneboy1 said:
[I was saying
(2/w)*sin(2*w/2) ≈ (2.pi/w)*sin(2*w/2.pi)
for reasons I cannot reckon]

Woops, good call, it should have been 't'less, I.e:
x(t) = (1/2pi)* ∫ (exp(jw)-exp(-jw) /2j)*exp(jwt) dw -∞ to ∞


Heh, heh, fairenough, Night.

Why are you trying to determine F-1{(sin(w)} anyway? Its inverse is not at all a common time function ...

If I had to do it I would study the way sin(wt) was transformed, then try to apply that technique to the inversion integral.
 

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