Several approaches come to mind, but each carries its own downfalls.
Waveform subraction: Will provide an estimate of the differences between
waveforms, but is extremely sensitive to any time offset.
Correlation coefficient: Analagous to a dot product of the voltage-time
sample points in each waveform. Doesn't capture absolute DC voltage level
shifts; r^2 offers no information about type of mismatch.
FFT: Can capture similarity in edge rates, ringing period, etc. but key
waveform differences may be masked or lost in high frequency noise seen in
FFT's of digital waveforms.
Overlaying and eyeballing: The human eye is an excellent image processing
device, but the statements "looks good" or "that's a lot of overshoot" are
often too subjective.
Apply basic metrics: Measuring rise/fall delay, ringback, over/undershoot,
ringing period, etc. are typically used. Again, however, the interpretation
of the matchup is subjective.
I'm not necessarily looking for a catchall solution, but would be
interesting in hearing about any novel approaches people are using.
Waveform overlay will still have its place, but it would be nice to combine
this with less subjective methods.
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