Effacer les filtres
Effacer les filtres

Dealing with NaN values in FFT

185 vues (au cours des 30 derniers jours)
noam edelshtein
noam edelshtein le 25 Juil 2020
Commenté : Star Strider le 9 Fév 2022
Hi, I'm working with a large data set of voxel information from MRI scans of multiple subjects, and as part of the analysis I use FFT. Prior to this, the data already goes through some modifications, removing specific values deemed too low (insignificant data) and replacing it with NaN values. After checking the results I realized there is an issue with FFT and NaN values. Is there some solution or workaround that someone perhaps knows that might help resolve this issue?

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Star Strider
Star Strider le 25 Juil 2020
If you have R2016b or later, the fillmissing function is an option.
  8 commentaires
Jon
Jon le 9 Fév 2022
Done, thanks for the reminder, I had forgotten about the upvoting feature.
Star Strider
Star Strider le 9 Fév 2022
Thank you!

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Plus de réponses (1)

Sugar Daddy
Sugar Daddy le 25 Juil 2020
what if you remove NaNs from dataset
Suppose
X = [1 2 3 NaN 3 2 1];
X(isnan(X)) = []
X =
1 2 3 3 2 1
  2 commentaires
noam edelshtein
noam edelshtein le 25 Juil 2020
That would cause a change in dimensions of the matrix, and there is more analysis to come after this stage, so I would need to know precisely where the nan values were to reinsert them in the right places following the fft analysis.
I considered replacing with 0 but I think that will cause some form of change in the results of the analysis.
Maya Eyal
Maya Eyal le 22 Fév 2021
I think this solution is not good, since it destroys the pattern in the data, and the whole reason we use the fft is to find the pattern.
I'm not an expert, just another one with the same NaN problem.
Unfortunatly, I use matlab 2019 so I don't have nufft function.
I'm not sure that interpulating the missing data will give me the pattern I want to find, but it seems I have no choice.

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