New Fast Optimal White-Noise Estimators for Deconvolution

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.