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Dealing with NaN values in FFT

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noam edelshtein
noam edelshtein 2020 年 7 月 25 日
コメント済み: Maya Eyal 2021 年 2 月 22 日
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?


Star Strider
Star Strider 2020 年 7 月 25 日
If you have R2016b or later, the fillmissing function is an option.
  4 件のコメント
Star Strider
Star Strider 2020 年 7 月 27 日
As always, my pleasure (here, and for the others as well)!


その他の回答 (1 件)

Sugar Daddy
Sugar Daddy 2020 年 7 月 25 日
what if you remove NaNs from dataset
X = [1 2 3 NaN 3 2 1];
X(isnan(X)) = []
X =
1 2 3 3 2 1
  2 件のコメント
Maya Eyal
Maya Eyal 2021 年 2 月 22 日
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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