Omatu, Sigeru and Seinfeld, John H.
(1981)
Filtering and Smoothing for Linear Discrete-Time Distributed Parameter Systems Based on Wiener-Hopf Theory with Application to Estimation of Air Pollution.
IEEE Transactions on Systems Man and Cybernetics, 11
(12).
pp. 785-801.
ISSN 0018-9472.
http://resolver.caltech.edu/CaltechAUTHORS:20140917-110121675
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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.
| Item Type: | Article |
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| Additional Information: | © 1981 IEEE. Manuscript received February 3, 1981; revised August 3, 1981. This work was supported by NASA Research Grant NAG 1-71. |
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| Group: | Environmental Quality Laboratory |
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| Funders: | | Funding Agency | Grant Number |
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| NASA | NAG 1-71 |
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| Other Numbering System: | | Other Numbering System Name | Other Numbering System ID |
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| Environmental Quality Laboratory | A-104 |
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| Record Number: | CaltechAUTHORS:20140917-110121675 |
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| Persistent URL: | http://resolver.caltech.edu/CaltechAUTHORS:20140917-110121675 |
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| Official Citation: | Omatu, S.; Seinfeld, John H., "Filtering and Smoothing for Linear Discrete-Time Distributed Parameter Systems Based on Wiener-Hopf Theory with Application to Estimation of Air Pollution," Systems, Man and Cybernetics, IEEE Transactions on , vol.11, no.12, pp.785,801, Dec. 1981
doi: 10.1109/TSMC.1981.4308618 |
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| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. |
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| ID Code: | 49779 |
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| Collection: | CaltechAUTHORS |
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| Deposited By: |
Ruth Sustaita
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| Deposited On: | 17 Sep 2014 18:36 |
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| Last Modified: | 26 Sep 2017 21:24 |
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