Recursive Bayesian estimation: Difference between revisions

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== Model ==

The true state <math>x</math> is assumed to be an unobserved [[Markov process]], and the measurements <math>z</math> are the observed states of a [[Hidden Markov Model]] (HMM). The following picture presents a Bayesian Network of a HMM.

[[Image:HMM_Kalman_Filter_Derivation.svg|center|Hidden Markov Model|center]]

Because of the Markov assumption, the probability of the current true state given the immediately previous one is conditionally independent of the other earlier states.