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Currently I am measuring data (Counts over Time).

Due to measurement problems I have some nasty peaks in this data. These peaks are periodical, very sharp (~3 datapoints over a range of 10000) and about 3 times higher than the normal noise ('delta-peaks'):

......|......|......|......|......|......

Currently we just clear these values out by setting these to NaN (not a number).

I think this is a typical solution by physicists and you would find a more elegant way.

I thought about Fourier filter, but since these peaks are very sharp the Fourier transform has periodic 'delta-peaks', too.

Do you have an idea how to solve this problem?

Thanks a lot.

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    actually I think the delta-noise is not that simple. I think that the peak height of these peaks is dependent on the change in the signal. The ratio and difference for the constant background between delta peak and noise is not the same as the ratio and difference between real peaks and delta peaks in the signal. Conclusion: I really don't know how the model would look like. That's why I wanted to apply a filter that is not directly depending on the height of the delta-peaks2012-10-09

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