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New Fast Optimal White-Noise Estimators for Deconvolution

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2 Author(s)
Jerry M. Mendel ; Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90007 ; John Kormylo

We present a brief qualitative discussion of Kalman filtering as contrasted with Wiener filtering, since the Kalman filter is an integral element in our new fast optimal white-noise estimators. Additionally, we present two fast algorithms, one of which is shown to be very efficient for calculating fixed-interval estimates of the reflection coefficient sequence, the other of which is shown to be very efficient for calculating either fixed-point or fixed-lag estimates of that sequence. Detailed operation counts are given which support these claims. Flow charts are also given for the Kalman filter and the two new fast smoothing algorithms.

Published in:

IEEE Transactions on Geoscience Electronics  (Volume:15 ,  Issue: 1 )