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The problem of state estimation and system structure detection for discrete stochastic dynamical systems with parameters which may switch among a finite set of values is considered. The switchings are modelled by a Markov chain with known transition probabilities. A brief survey and a unified treatment of the existing suboptimal algorithms are provided. The optimal algorithms require exponentially increasing memory and computations with time. Simulation results comparing the various suboptimal algorithms are presented.
J.K. Tugnait (Tue,) studied this question.