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How does output DBFS relate to spectrum analysis?
Old 2 weeks ago
  #1
How does output DBFS relate to spectrum analysis?

Hello,
I am curious to know how a signal's output DBFS relates to frequency spectrum in a visual spectrum analyzer. For example, when analyzing a song using the Span plugin, the max DBFS is just below zero, but the max of any frequency band in the graph is no more than -18db. I assume the output DBFS is much higher as it is the summation of all the frequency bands?
Old 5 days ago
  #2
Quote:
Originally Posted by sambaji ➡️
Hello,
I am curious to know how a signal's output DBFS relates to frequency spectrum in a visual spectrum analyzer. For example, when analyzing a song using the Span plugin, the max DBFS is just below zero, but the max of any frequency band in the graph is no more than -18db. I assume the output DBFS is much higher as it is the summation of all the frequency bands?
Do you know?
Old 5 days ago
  #3
I'm not sure this has much practical studio value, but if you perform a numeric integration of all the raw FFT bin values from the spectrograph (not the dB, but the numeric FFT sample bin values) across the frequency spectrum, and the FFT has zero slope, the result is the sample value of the output, for any given discrete (clock time division) instant.

To convert integer sample values:
dBFS = 20 log(sample value / (2^(wordsize-1)))
To get a sample value from dBFS, use the inverse of the equation.
The "-1" is for the sign bit.

That's the general idea. If I have an error in this somewhere, I'm confident somebody will post a correction.
Old 5 days ago
  #4
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Old 2 days ago | Show parent
  #5
Quote:
Originally Posted by Philbo King ➡️
I'm not sure this has much practical studio value, but if you perform a numeric integration of all the raw FFT bin values from the spectrograph (not the dB, but the numeric FFT sample bin values) across the frequency spectrum, and the FFT has zero slope, the result is the sample value of the output, for any given discrete (clock time division) instant.

To convert integer sample values:
dBFS = 20 log(sample value / (2^(wordsize-1)))
To get a sample value from dBFS, use the inverse of the equation.
The "-1" is for the sign bit.

That's the general idea. If I have an error in this somewhere, I'm confident somebody will post a correction.
Thanks. While it may not have practical studio implications, it's still good to understand how our tools work.
Old 1 day ago
  #6
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Quote:
Originally Posted by sambaji ➡️
I am curious to know how a signal's output DBFS relates to frequency spectrum in a visual spectrum analyzer.
Frequency spectrum is showing the level of individual frequency components of the signal. If you add all the components together, you get the original signal. That's why the RMS of the overall signal is the sum of energies of individual FFT components. On the other hand, peak levels of the signal can't be deduced from the FFT spectrum, because they also depend on phase, which is not shown by spectrum analyzers.
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