I would like to extract the location of data jump (see figure below), the difficulty is that the data are noisy as you can see. I try with a median filter or a other regularization and it could move the location of my jump.

Perhaps i could compute differences between consecutive data and then extract the most important one. Nonetheless my data could contain two jumps... And for information I m working with Python

enter image description here

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    $\begingroup$ Take a look at this related question and its answers. $\endgroup$
    – Matt L.
    Jul 18, 2018 at 10:54
  • $\begingroup$ Is something wrong with my answer? $\endgroup$ Sep 7, 2018 at 11:46

1 Answer 1


Use a low-pass filter with linear phase. Since group delay is the derivative of phase over frequency, linear phase filters have constant group delay.

That way, yes, you shift that jump, but simply by subtracting the group delay, you get the original position.

Group delay for a discrete causal filter is half its length.


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