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First I introduce a set of important variables that will help us
build the desired filters.
- 9#9: the data vector; input to the problem.
- 344#344: the noise vector; assumed to be known.
- 343#343: the signal vector; output of the problem.
- 110#110: annihilation filter for the data; a Prediction
Error Filter (PEF).
- 366#366: annihilation filter for the noise; a PEF.
- 367#367: annihilation filter for the signal; a PEF.
The leading assumption is that the data vector is the sum of the signal
and noise vectors, i.e,
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Stanford Exploration Project
6/7/2002