- Discard NaN's
- Fill the NaN's using interpolation (interp1, spline)
- Fill the NaN's using fillmissing
- Fill the NaN's using fillgaps
How can I compute spectrogram for data vector containing NaN values?
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Dear community,
I am currently working on seismic recordings and I need to compute the spectrogram. The dataset has been cleaned in advance, and thus the original vector contains small portions of NaN values (about a few seconds each with a sample rate of 100 Hz).
However, spectrogram function cannot be applied to NaN values without compromising the entire result, and applying it to not NaN values (applied to data(~isnan(data)) would provide incorrect results (spectrogram function assumes that the sample rate is homogeneous which would no longer be the case).
I do not really know how to manage this issue, and to compute a correct power spectral density for my data, if anyone has a clue...
Thank you
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