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Abstract
The Kalman filter is applied to the inverse filtering or deconvolution problem. The derivation given of the Kalman filter emphasizes the relationship between the Kalman and Wiener filter. This derivation is based on the representation of systems by state variables and the modeling of random processes as the output of linear systems excited by white noise. Illustrative results indicate the applicability of these techniques to a variety of geophysical data processing problems. The Kalman filter offers exploration geophysicists additional insight into processing‐problem modeling and solution.
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