Linear recursive discrete-time estimators using covariance information under uncertain observations

DOI10.1016/S0165-1684(03)00056-2zbMath1144.93375OpenAlexW2038958420WikidataQ59552621 ScholiaQ59552621MaRDI QIDQ948159

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

Publication date: 8 October 2008

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-1684(03)00056-2

zbMATH Keywords

stochastic processlinear discrete-time systemsWiener-Hopf equationrecursive estimationcovariance information

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11)

Related Items (6)

Optimal linear estimation for systems with multiple packet dropouts ⋮ Derivation of linear estimation algorithms from measurements affected by multiplicative and additive noises ⋮ Recursive estimators of signals from measurements with stochastic delays using covariance information ⋮ Signal estimation with nonlinear uncertain observations using covariance information ⋮ Linear minimum variance estimators for systems with bounded random measurement delays and packet dropouts ⋮ Distributed asynchronous fusion algorithm for sensor networks with packet losses

This page was built for publication: Linear recursive discrete-time estimators using covariance information under uncertain observations