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Particle-Filter-Dynamic-Bayesian-network

Scalar random process is given with the model:

Model

where wt and vt are white Gaussian noises with variances 10 and 1.

Process is simulalted for 50 time steps, and for inital state X0 = 0.1 the aposterior distribution p(xt|e1:t) is evaluated using the Particle Filter. Optimal number of particles is found by calculating MSE.

RESULTS

results MSE histogram

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