Filtering and Smoothing for Linear Discrete-Time Distributed Parameter Systems Based on Wiener-Hopf Theory with Application to Estimation of Air Pollution

DOI10.1109/TSMC.1981.4308618zbMath0467.93061OpenAlexW2058799734MaRDI QIDQ3921115

John H. Seinfeld, Shigeru Omatu

Publication date: 1981

Published in: IEEE Transactions on Systems, Man, and Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tsmc.1981.4308618

zbMATH Keywords

smoothingfixed-pointfilteringWiener-Hopf theoryestimation of air pollutionlinear discrete-time distributed parameter systemsfixed- intervalfixed-lag smoothersleast-squares estimation error criterionoptimal smoothing estimators

Mathematics Subject Classification ID

Gaussian processes (60G15) Filtering in stochastic control theory (93E11) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05) Environmental economics (natural resource models, harvesting, pollution, etc.) (91B76)

Related Items (4)

On the relationship between the Lagrange multiplier method and the two-filter smoother ⋮ Suboptimal state estimation algorithm for non-linear discrete-time distributed-parameter systems ⋮ Estimation of nitrogen dioxide concentrations in the vicinity of a roadway by optimal filtering theory ⋮ Optimal estimators for time-averaged measurement systems

This page was built for publication: Filtering and Smoothing for Linear Discrete-Time Distributed Parameter Systems Based on Wiener-Hopf Theory with Application to Estimation of Air Pollution