Please use this identifier to cite or link to this item:
http://hdl.handle.net/2282/387
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| Title: | Dynamic system multivariate calibration with low-sampling-rate y data |
| Authors: | Ergon, Rolf
Halstensen, Maths |
| Issue Date: | 2000 |
| Publishers version: | http://dx.doi.org/10.1002/1099-128X(200009/12)14:5/6<617::AID-CEM618>3.0.CO;2-M |
| Abstract: | When the data in principal component regression (PCR) or partial least squares regression (PLSR) form time
series, it may be possible to improve the prediction/estimation results by utilizing the correlation between
neighboring observations. The estimators may then be identified from experimental data using system
identification methods. This is possible also in cases where the response variables in the experimental data are
sampled at a low and possibly irregular rate, while the regressor variables are sampled at a higher rate. After a
discussion of the options available, the paper shows how the autocorrelation of the regressor variables in such
multirate sampling cases may be utilized by identification of parsimonious output error (OE) estimators. An
example using acoustic power spectrum regressor data is finally presented. |
| Keywords: | Dynamic
Multivariate
Calibration
Multirate |
| Publisher: | Wiley |
| Document type: | Journal article |
| URI: | http://hdl.handle.net/2282/387 |
| Appears in Collections: | Institutt for elektro, IT og kybernetikk
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