An Interesting Fourier Transform – 1/F Noise

(dsprelated.com)

61 points | by q7m 3 days ago

5 comments

  • threatripper 2 hours ago
    1/f noise basically kills averaging. You collect more signal but at the same time equally more noise.
    • rcxdude 2 hours ago
      Yup, it has the fun property that you'll get the same error in your estimate of the mean regardless of averaging time (though since it's not stationary this isn't even really that well defined).

      (though of course, a random walk means you'll get even worse as you measure for longer...)

  • lars 4 hours ago
    The comment section at the bottom of the article is pretty interesting. 20 years of people thinking about this.
    • AnthonBerg 1 hour ago
      As noise, its 1/f is 0.748544393 years per comment, haha.

      (The frequency is 42.3338481 nanohertz.)

  • mturmon 5 hours ago
    The piece ends with the observation that maybe the fact that 1/f noise is its own Fourier transform is a clue.

    Turns out this property is not unusual. There are many such pairs - there’s a reasonably well-known journal paper with a construction technique.

    • fch42 5 hours ago
      The paper linked at the "see also" section ? (thx)
  • TeMPOraL 4 hours ago
    Just as interesting and surprising to me is that this 0-100Hz line is unexplained. Given that signal processing is the foundation of pretty much all digital technology, as well as the analog technologies that came before, I've kind of assumed every segment of a frequency plot be well studied and understood, with half a dozen of names to choose for (doublesine quefrency this, Kowalski-Shannon that...) and a heap of decades old textbooks about it.

    I confirm, the low frequency range looks weird on every DFT plot I ever saw, particularly the audio ones. I just assumed it has something to do with ADC and is probably explained on Wikipedia. It's literally one of the last place on Earth when I'd expect to find unsolved mysteries.

    • rcxdude 4 hours ago
      It's not completely unexplained. Roughly speaking you can get that power spectrum in the limit when you are adding up many different events where the magnitude of the event is inversely proportional to its likelihood (and in practice, there is a limit to the magnitude of the events that will cause it to level off at some point, but for some processes this is not measurable even over decades). The main mystery in most cases is what exactly is the physical process that is causing it. For some electronics it looks like it is due to trapped charges sometimes tunneling around, but it doesn't explain every case of it in electronics let alone everything else. Convective thermal effects can also be a good candidate in a lot of systems, since turbulence also has 1/f noise properties.

      (Also, the low frequency range on a DFT can look weird for reasons other than noise: it'll also tend to rise up if there's any longer-term structure to the signal as well, so you need to be careful interpreting them blindly if you're trying to measure noise)

    • tiazumdove 2 hours ago
      Low frequencies are studied quite extensively, especially the mHz-10Hz region for noise characterization of solid state materials. 1/f is quite well studied depending on your field. In semiconductor physics, for example, one possible explanation is electrons trapped in defects or on charged islands and then slowly trickling down. Of course this explanation cannot be used in other fields where 1/f noise shows up as well. The problem is that no model gives a satisfying answer as to why it occurs therefore its unexplained. Lack of model doesn't mean that you can't engineer your way around 1/f noise for example the chopper amp works so well because it shifts away towards frequencies above the 1/f cutoff.
    • analog31 13 minutes ago
      Compounding the mystery is that it crops up everywhere, not just electronic noise plots. But outside of a few systems such as electronic noise in a laboratory setting, it's phenomenally hard to measure. For one thing, to get into the 1/f domain, you have to measure things for a long time. And the noise measurement itself is noisy. And the number of things that you need to control, such as environmental conditions, increases.

      So its existence is often largely treated as an empirical rule of thumb rather than having a specific physical cause.

  • tgv 3 hours ago
    Wikipedia has an article with some other information on pink noise (a more common name), including a random generator: https://en.wikipedia.org/wiki/Pink_noise. Some music generation algorithms use pink noise, as it (supposedly) strikes a better balance between randomness and predictability.
    • rcxdude 3 hours ago
      Pink noise is also perceptually flat noise, because it contains the same energy in each octave (or decade). 'truly' white noise (equal energy for equal bandwidth) tends to sound quite tinny/hissy in comparison.
      • kadoban 2 hours ago
        I went through a phase of using ~whitenoise while working to block out distractions.

        Actual white noise indeed sounds really bad and grating. The best for me was a mix of pink and brown noise, pink for an ~equal baseline and brown to make it sound a little more mellow.

        I suspect most/all generators meant to block out noise do something similar. It really sounds pretty bad without that, especially for anything more than a few seconds.

        • rcxdude 2 hours ago
          Yeah. pink noise is often confused with white noise in audio because it looks flat on a lot of equaliser displayers (because they show energy per octave instead of energy per Hz).