


 Decon comparisons between Burg and conjugategradient methods  

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Decon comparisons between Burg and conjugategradient methods
Antoine Guitton and Jon Claerbout
Abstract:
In testing on several nearby data sets, three shown here,
the Burg method of deconvolution exhibited no issues of numerical roundoff.
In every case it did exhibit whiteness, an aspect of the theory normally considered desirable.
Predictionerror code based on conjugate gradients
(actually conjugate directions) showed some minor issues.
Output comparisons of the two were never perceptibly different on paper documents such as this.
When those same PDF documents are viewed on a screen,
differences might be noticeable with ``blink'' screen presentation.
Doing no more than the number of iterations theoretically predicted
(equal to the number of filter coefficients)
gave differences generally noticeable with blink presentation.
Tripling the number of iterations made the differences
much smaller, sometimes differing at a mere handful of pixels.
Although discrepancies were minuscule on the filtered data,
the differences are quite clear in a spectral comparison.
Differences tend to occur at the very high and very low frequencies that are weak in the field data.



 Decon comparisons between Burg and conjugategradient methods  

Next: INTRODUCTION
Up: Reproducible Documents
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