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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Weiwu Yan Huihe Shao Xiaofan Wang |
| Copyright Year | 2003 |
| Description | Author affiliation: Dept. of Autom., Shanghai Jiao Tong Univ., China (Weiwu Yan; Huihe Shao; Xiaofan Wang) |
| Abstract | This paper proposes a novel data reconciliation method based on Kernel Principal Component Analysis (KPCA). In the proposed method, essential information of nonlinear system is extracted by KPCA. Then the data is reconstructed by small count of important nonlinear principle components, which represent essential information of nonlinear system, and noise is removed from reconciliated data. The proposed method is applied to nonlinear data reconciliation of ternary distillation column. Effective results show that proposed method provides a new method for nonlinear data reconciliation. |
| Sponsorship | American Automatic Control Council IFAC |
| Starting Page | 2503 |
| Ending Page | 2504 |
| File Size | 155702 |
| Page Count | 2 |
| File Format | |
| ISBN | 0780378962 |
| ISSN | 07431619 |
| DOI | 10.1109/ACC.2003.1243452 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-06-04 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Kernel Principal component analysis Eigenvalues and eigenfunctions Nonlinear equations Distillation equipment Pollution measurement Nonlinear systems Matrices Least squares approximation Automation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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