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State and parameter estimation of state-space model with entry-wise correlated uniform noise. (English) Zbl 1338.93358
Summary: Joint parameter and state estimation is proposed for linear state-space model with uniform, entry-wise correlated, state and output noises (LSU model for short). The adopted Bayesian modelling and approximate estimation produce an estimator that (a) provides the maximum a posteriori estimate enriched by information on its precision, (b) respects correlated noise entries without demanding the user to tune noise covariances, and (c) respects bounded nature of real-life variables.

MSC:
93E10 Estimation and detection in stochastic control theory
93E11 Filtering in stochastic control theory
93E03 Stochastic systems in control theory (general)
93C55 Discrete-time control/observation systems
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