Abstract
The linear filtering, prediction, and smoothing problems are treated for linear message processes with state-dependent noise and time-correlated measurement noise. In particular, a general smoothing formula for these classes of message processes is developed. The derivation evolves directly from the Wiener-Hopf equation and does not use the innovations process.
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