> If you want to detect clipping, you want to know if the magnitude of any
> sample is greater than 1.0 — that's all there is to it. No FFT. My code
> happens to divide the stream into vectors but that is the only similarity.
>
> Performing a FFT will not help you detect clipping. To illustrate this:
> suppose your signal content is a bunch of different sine waves of
> constant amplitude and slightly different frequencies. The maximum
> sample magnitude in the combined signal will occur when the phases of
> all those sines align, which will happen periodically. But the FFT's job
> is to separate out those sines into independent bins of constant
> amplitude. A signal that clips and one that doesn't can look very
> similar in the frequency domain, but in the time domain the difference
> is obvious because you're looking /directly at what matters/ — the
> sample values that are (after scaling) being sent to the DAC.
That all makes sense. But if you are looking at the raw IQ stream, with
two values per sample, do you just look to see if either the I or the Q
hits 1, or do you need to manipulate both components of the complex
number to get a real number?
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