Abstract
Nonlinear filtering problem for discrete-time systems with random structure is treated by the systematic use of Bayes approach. The main result lies in difference equations for the posterior distribution of the system state and structure index which can serve as a basis for any optimal or suboptimal filter construction. The optimal filtering equations have such a structure that even in the linear Gaussian case optimal finite-dimensional filters do not exist. An approximate filtering problem is considered.
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