Chandrasekhar-type recursive Wiener estimation technique in linear discrete-time stochastic systems

DOI10.1016/J.AMC.2006.11.021zbMath1130.93419OpenAlexW2021937016MaRDI QIDQ2372046

Seiichi Nakamori

Publication date: 10 July 2007

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

Full work available at URL: https://doi.org/10.1016/j.amc.2006.11.021

zbMATH Keywords

Wiener-Hopf equationdiscrete-time stochastic systemRLS Wiener filtercovariance informationwide-sense stationarityChandrasekhar-type filter

Mathematics Subject Classification ID

Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05) Least squares and related methods for stochastic control systems (93E24)

Cites Work

• Unnamed Item
• Scattering theory and linear least squares estimation. II: Discrete-time problems
• Chandrasekhar-type filter using covariance information for white Gaussian plus colored observation noise.
• Chandrasekhar-type filter for a wide-sense stationary signal from uncertain observations using covariance information
• Some new algorithms for recursive estimation in constant linear systems
• Extended Levinson and Chandrasekhar equations for general discrete-time linear estimation problems
• Some new algorithms for recursive estimation in constant, linear, discrete-time systems

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