Second-order polynomial estimators from uncertain observations using covariance information

DOI10.1016/S0096-3003(02)00364-8zbMath1026.62096DBLPjournals/amc/NakamoriCHL03OpenAlexW2107875745WikidataQ59552652 ScholiaQ59552652MaRDI QIDQ1399797

Seiichi Nakamori, Raquel Caballero-Águila, Josefa Linares-Pérez, Aurora Hermoso-Carazo

Publication date: 30 July 2003

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0096-3003(02)00364-8

zbMATH Keywords

Wiener-Hopf equationcovariance informationuncertain observationsinnovation approachsecond-order polynomial estimation

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20)

Related Items (9)

Quadratic estimation from uncertain observations with white plus coloured noises using covariance information ⋮ Nearest-neighbour modelling of reciprocal chains ⋮ Design of quadratic estimators using covariance information in linear discrete-time stochastic systems ⋮ Quadratic estimation problem in discrete-time stochastic systems with random parameter matrices ⋮ Polynomial fixed-point smoothing of uncertainly observed signals based on covariances ⋮ New recursive estimators from correlated interrupted observations using covariance information ⋮ Least-squares \(\nu\) th-order polynomial estimation of signals from observations affected by non-independent uncertainty ⋮ Fixed-interval smoothing problem from uncertain observations with correlated signal and noise ⋮ Quadratic estimation of multivariate signals from randomly delayed measurements

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• Polynomial estimation of the amplitude of a signal
• Optimal quadratic filtering of linear discrete-time non-Gaussian systems
• Recursive Bayesian estimation with uncertain observation (Corresp.)
• Optimal quadratic solution for the non-Gaussian finite-horizon regulator problem

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