Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published December 1981 | Published
Journal Article Open

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

Abstract

Optimal filtering and smoothing algorithms for linear discrete-time distributed parameter systems are derived by a unified approach based on the Wiener-Hopf theory. The Wiener-Hopf equation for the estimation problems is derived using the least-squares estimation error criterion. Using the basic equation, three types of the optimal smoothing estimators are derived, namely, fixed-point, fixed-interval, and fixed-lag smoothers. Finally, the results obtained are applied to estimation of atmospheric sulfur dioxide concentrations in the Tokushima prefecture of Japan.

Additional Information

© 1981 IEEE. Manuscript received February 3, 1981; revised August 3, 1981. This work was supported by NASA Research Grant NAG 1-71.

Attached Files

Published - A-104.pdf

Files

A-104.pdf
Files (4.3 MB)
Name Size Download all
md5:7d01eda373cd2957b6aca446b0741198
4.3 MB Preview Download

Additional details

Created:
August 19, 2023
Modified:
October 17, 2023