Why can a smooth function be described with fewer terms in a Fourier series?

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Discussion Overview

The discussion revolves around the characteristics of Fourier series and transforms, particularly focusing on why smoother functions can be represented with fewer terms compared to less smooth functions. Participants explore the implications of function smoothness on the frequency components in both periodic and non-periodic contexts.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant suggests that less smooth functions, such as those with sharp changes or discontinuities, lead to a more spread out Fourier transform, implying that higher frequency components are needed to represent them.
  • Another participant notes that smooth and slowly changing functions can be adequately described with fewer terms in a Fourier series, questioning whether this is due to the nature of the derivatives of the terms in the series.
  • A participant raises a related question about evaluating the infinite integral of the complex exponential function to represent the Dirac delta function, indicating a connection to the original topic.
  • There is a clarification that the number of non-zero terms in a Fourier series is distinct from their frequencies, and a suggestion to avoid ambiguous terminology like "nasty function." Participants are encouraged to differentiate between Fourier transforms and Fourier series.

Areas of Agreement / Disagreement

Participants express differing views on the terminology and concepts related to Fourier series and transforms. There is no consensus on the implications of smoothness versus non-smoothness in function representation, and the discussion remains unresolved regarding the best way to articulate these ideas.

Contextual Notes

Participants highlight the need for clarity in distinguishing between different types of Fourier representations and the mathematical nuances involved, such as the treatment of derivatives and the nature of function smoothness.

Nikitin
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Hi! I am taking a second look on Fourier transforms. While I am specifically asking about the shape of the Fourier transform, I'd appreciate if you guys could also proof-read the question below as well, as I've written down allot of assumptions that I've gained, which might be wrong.

OK.

As far as I am aware, the nastier/"less smooth" (ie sharp, large and discontinious derivative and so on) a function ##f(x)## is (for ex. ##f(x) = \delta (x)##, the more "spread out" its Fourier transform is. That is, the sines and cosines summed by the fourier-inverse integral get weighed increasingly equally regardless of their frequencies, as ##f(x)## becomes less periodic.

However if you got a very spread out and slowly changing ##f(x)## (for ex. ##f(x)=1##), the Fourier transform will be narrow around 0, meaning only the low-frequency sines and cosines in the fourier-inverse integral will dominate.

Why is this so? This applies to periodic functions as well, so let me rephrase the question in case you don't get me: Why can a "smooth and slow" function be described adequately with less terms in a Fourier series, than a nasty one? Is it perhaps because the further you go out in a Fourier series, the bigger the derivatives will be and thus these violent sines and cosines can adequately describe a swiftly changing function?
 
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And can somebody tell me how to evaluate the infinite integral of the complex exponential function so I can get something representing the dirac delta? (I didn't want to open a new thread for this question alone as it's related to the OP, so don't murder me moderators).

I read that you can multiply it a converging term as a trick, like this, ##\lim_{\epsilon \to 0} \int_{-\infty}^{\infty} e^{-\epsilon x^2} \cdot e^{isx} dx##, but I don't remember how to evaluate a gaussian integral multiplied by another function.
 
Nikitin said:
And can somebody tell me how to evaluate the infinite integral of the complex exponential function so I can get something representing the dirac delta? (I didn't want to open a new thread for this question alone as it's related to the OP, so don't murder me moderators).

I read that you can multiply it a converging term as a trick, like this, ##\lim_{\epsilon \to 0} \int_{-\infty}^{\infty} e^{-\epsilon x^2} \cdot e^{isx} dx##, but I don't remember how to evaluate a gaussian integral multiplied by another function.

##\int_{-\infty}^{\infty} e^{-\epsilon x^2} \cdot cos(sx) dx=\sqrt{{\pi}/{\epsilon}}\cdot e^{{-s^2}/{4\epsilon}}##, from Gradshteyn and Ryzhik. Note that the imaginary part = 0.
 
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Nikitin said:
Why can a "smooth and slow" function be described adequately with less terms in a Fourier series, than a nasty one? Is it perhaps because the further you go out in a Fourier series, the bigger the derivatives will be and thus these violent sines and cosines can adequately describe a swiftly changing function?
You confuse two things: number (amount) of non-zero terms, and their frequencies (i.e. this n in your \cos nx and \sin nx or, in the standard presentation, \exp(inx)).

Also,
  • Do not use such terms as “nasty function”. Not clear.
  • Make distinction between Fourier transform of functions on ℝ and Fourier series on the circle (a.k.a. for periodic functions).
  • Learn to think in exponents, not ugly real trigonometry.
 

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