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In the case of randomly missing traces in regularly sampled data,
a prediction-error filter cannot be found.
This section explains an alternative way to find a filter
whose spectrum is the inverse of the given data's spectrum.
If there exist several linear events in a data set, the zeros which were
found by the prediction-error filter would locate along the dips
in the spectrum.
If we know the dips of the events, therefore, we can simulate
the prediction-error filter by putting zeros along the dips in the spectrum.

Suppose we have *N* plane waves and each dip is *p*_{j}, *j*=1,...,*N*,
respectively.
For each frequency , then, *N* zeros along the wavenumber
are determined as follows :

and the corresponding zeros are
From those zeros, the prediction-error filter for each is determined
in the form of the Z transform like

** Next:** Interpolation
** Up:** THREE STEP INTERPOLATION
** Previous:** Dip picking
Stanford Exploration Project

11/18/1997