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A new method for the dual estimation in state-space dynamic model was described, with a focus on sequential Bayesian learning about time-varying state and static parameters simultaneously. The new algorithm combines auxiliary particle filtering (APF) with particle swarm optimization (PSO) to achieve computational efficiency and stability. By properly choosing the fitness function of PSO, the algorithm...
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