State and parameter estimation of state‐space model with entry‐wise correlated uniform noise | Zendy

Pavelková Lenka | Zendy; Kárný Miroslav | Zendy

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State and parameter estimation of state‐space model with entry‐wise correlated uniform noise

Author(s) -

Pavelková Lenka,

Kárný Miroslav

Publication year - 2014

Publication title -

international journal of adaptive control and signal processing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.73

H-Index - 66

eISSN - 1099-1115

pISSN - 0890-6327

DOI - 10.1002/acs.2438

Subject(s) - estimator , noise (video) , state (computer science) , bounded function , state space , state space representation , estimation , bayes estimator , estimation theory , mathematics , a priori and a posteriori , space (punctuation) , bayesian probability , maximum a posteriori estimation , computer science , maximum likelihood , algorithm , statistics , artificial intelligence , engineering , mathematical analysis , philosophy , systems engineering , epistemology , image (mathematics) , operating system

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. Copyright © 2013 John Wiley & Sons, Ltd.

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