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Variance

In the above example, the assumption that the variance of our noise is spatially invariant is correct. In a more general problem, this will not be the case. As a result, a more appropriate formulation for our noise covariance is
\begin{displaymath}
\bf N= \bf N_c \bf N_v .\end{displaymath} (11)
In this formulation, $\bf N_c$ is a description of the relation between points. It will take the form of a PEF or one of the other operators described above. The second operator $\bf N_v$ will attempt to normalize the variance of the various data errors to the same level and should be equal to
\begin{displaymath}
N(i)=\sqrt { \frac{1}{V(i)}} ,\end{displaymath} (12)
where V(i) is the variance at a given data location i.
next up previous print clean
Next: and Up: PROBLEMS Previous: Inverse noise covariance
Stanford Exploration Project
7/8/2003