EQUIVALENCE-MOTIVATED NON-LINEAR RECURSIVE ESTIMATION

Recursive non-linear Bayesian estimation is addressed using equivalence approach as motivating framework. Its specific form - tailored to a model class covering non-normal ARX (auto-regression with exogenous variables) models, models with discrete outputs and continuous-valued regression vectors and their dynamic mixtures - is presented. The resulting algorithms provide efficient solutions of difficult and practically important estimation problems.