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Summing up the ideas above,
we start from fitting goals
| ![\begin{displaymath}
\begin{array}
{lll}
\bold 0 &\approx& \bold F \bold m \ -\ \bold d \\ \bold 0 &\approx& \bold A \bold m\end{array}\end{displaymath}](img35.gif) |
(8) |
and we change variables from
to
using
| ![\begin{displaymath}
\begin{array}
{llllcl}
\bold 0 &\approx & \bold F \bold m \ ...
...d 0 &\approx & \bold A \bold m &=& \bold I & \bold p\end{array}\end{displaymath}](img37.gif) |
(9) |
Preconditioning means iteratively fitting
by adjusting the
variables
and then finding the model by using
.A new reusable
preconditioned solver is
the module solver_prc
.
Likewise the modeling operator
is called Fop
and the smoothing operator
is called Sop.
Details of the code are only slightly different from
the regularized solver
solver_reg
.
solver_prcPreconditioned solver
Next: OPPORTUNITIES FOR SMART DIRECTIONS
Up: PRECONDITIONING THE REGULARIZATION
Previous: Statistical interpretation
Stanford Exploration Project
4/27/2004