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Example

In a first example, we applied the method to deconvolution on the helix Claerbout (1997) using the factors obtained with the Wilson-Burg spectral factorization. We take the auto-correlation to be the negative of the Laplacian operator, and convolve it with a spike placed in the middle of each panel in Figure 3. We use the Wilson-Burg method to find the wavelet with this auto-correlation and then deconvolve (do polynomial division) on the helix to find back the input spike.

 
autolapfac
autolapfac
Figure 3
Wilson factorization of the Laplacian. From left to right: the input filter; its auto-correlation; the factors obtained with the Wilson-Burg method; the result of the deconvolution using the Wilson-Burg factors.
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In another example, we analyzed the rate of convergence of the Wilson-Burg method. We selected a simple polynomial which is the cross-correlation of two triangle functions,
\begin{displaymath}
4/Z+15+11Z+7Z^2+3Z^3 = 12\;
\left(1+\frac{1}{3Z}\right)
\left(1+\frac{3}{4}Z+\frac{1}{2}Z^2+\frac{1}{4}Z^3\right) \end{displaymath} (14)
Table 1 shows the quadratic rate of convergence, defined using a relation similar to equation (8) for the coefficients of the two factors, A and B.


 
Table 1: Convergence rate
iter A B
1 0.0364715122 0.0442032255
2 0.0029259326 0.0002011458
3 0.0000014305 0.0000000199
4 0.0000000894 0.0000000199
5 0.0000000596 0.0000000000
6 0.0000000000 0.0000000000


next up previous print clean
Next: Conclusions Up: Spectral factorization: Sava, et Previous: Discussion
Stanford Exploration Project
7/5/1998