1. A system for analyzing a dynamic system model using Bayesian filtering, the system comprising: a prediction module for predicting a state model of the dynamic system model from a prior density and the dynamic system model, the prediction module generating a prediction density having at least one mode, the representation of the prediction density including at least one kernel; an approximating module for approximating at least one measurement likelihood function from a sample set through at least one kernel; an update module for updating a conditional density function using the measurement likelihood function and the prediction density; and a mode finding and mixture reduction module for reducing the number of kernels in a probability density distribution function.