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12<br />

(c) The estimate for m is then ̂m = ̂x + m 0 .<br />

Implement several realizations of missing data interpolation using several realizations<br />

of m 0 . You can do it by modifying either SConstruct or interpolate.c.<br />

5. Include your results in the paper.<br />

6. EXTRA CREDIT for implementing missing data interpolation using the FFT<br />

method for model covariance.<br />

COMPLETING THE ASSIGNMENT<br />

1. Change directory to hw5.<br />

2. Edit the file paper.tex in your favorite editor and change the first line to have<br />

your name instead of Bayes’s.<br />

3. Run<br />

sftour scons lock<br />

to update all figures.<br />

4. Run<br />

sftour scons -c<br />

to remove intermediate files.<br />

5. Run<br />

scons <strong>pdf</strong><br />

to create the final document.<br />

6. Submit your result (file paper.<strong>pdf</strong>) on paper or by e-mail.<br />

REFERENCES<br />

Claerbout, J., 2008, Image estimation by example: Environmental soundings image<br />

enhancement: Stanford Exploration Project.<br />

Claerbout, J., and M. Brown, 1999, Two-dimensional textures and prediction-error<br />

filters: 61st Mtg., Eur. Assn. Geosci. Eng., Session:1009.<br />

Marcotte, D., 1996, Fast variogram computation with FFT: Computers and Geosciences,<br />

22, 11751186.

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