Fourier transform, same frequencies, different amplitudes

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Discussion Overview

The discussion revolves around the behavior of Fourier transforms (FT) when dealing with sine waves that have the same frequencies but different amplitudes. Participants explore the implications of this scenario in both continuous and discrete Fourier transforms, focusing on how these amplitudes affect the final result.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant asks whether sine waves with similar frequencies but different amplitudes will be summed in the final Fourier transform result.
  • Another participant seeks clarification on whether the question pertains to the difference between functions with Fourier transforms that differ by a constant or the effect of different amplitudes within the same transform.
  • A participant explains that sine waves of different frequencies will produce peaks in the Fourier transform corresponding to their amplitudes, but the similarity of frequencies does not affect this outcome.
  • It is noted that two Fourier transforms with identical frequencies but different amplitudes correspond to different time-domain signals, and that the Fourier transform is a linear operator allowing for the addition of transforms frequency by frequency.
  • A later reply confirms that for a discrete Fourier transform, "similar" means close enough to be in the same bin, while for continuous Fourier transforms, "similar" means exact.

Areas of Agreement / Disagreement

Participants express differing views on the clarity of the original question and the implications of amplitude differences in Fourier transforms. There is no consensus on the interpretation of the effects of similar frequencies and differing amplitudes.

Contextual Notes

The discussion includes assumptions about the definitions of "similar" in the context of discrete versus continuous Fourier transforms, which remain unresolved.

Who May Find This Useful

Individuals interested in signal processing, Fourier analysis, or the mathematical properties of transforms may find this discussion relevant.

Behrouz
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I understand that the Fourier transform is changing the domain (time/space) to frequency domain and provides the sin waves. I have seen the visualizations of Fourier transform and they are all showing the transform results as the list of frequencies and their amplitude. My question is, what if the result has same sin waves with similar frequencies, but different amplitudes; are they going to be summed up (added/subtracted) in the final result?
 
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It is not really clear to me what your question is. Do you mean to ask what is the difference between two functions whose FTs differ by some constant or how different amplitudes in the same FT affect the result?
 
Orodruin said:
It is not really clear to me what your question is. Do you mean to ask what is the difference between two functions whose FTs differ by some constant or how different amplitudes in the same FT affect the result?
Thanks.
I mean the effect of different amplitudes (for similar frequencies) in the same FT.
 
Behrouz said:
Thanks.
I mean the effect of different amplitudes (for similar frequencies) in the same FT.
Sorry, but this is still not clear. If you have sine waves of different frequencies, each will lead to a peak at the corresponding frequency, the height of that peak will correspond to the amplitude of the sine wave, but the fact that frequencies are similar or not plays no role here.

Or are you talking about discrete Fourier transforms?
 
Two FTs with identical frequencies, but different amplitudes are associated with different signals in the time domain. If two time-domain signals are combined, their FTs can be added, frequency by frequency, to get the FT of the combined time-domain signal. That is because the FT is a linear operator.
 
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Behrouz said:
what if the result has same sin waves with similar frequencies, but different amplitudes; are they going to be summed up (added/subtracted) in the final result?

My short answer is yes.

My longer answer is that for a discrete FT similar means close enough to be in the same bin. For continuous FT, similar means exact.
 
Thank you all.
No, it wasn't specifically for DFT.
I believe @FactChecker 's answer is what I was looking for in this case.
Thanks again.
 

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