| 摘要 |
<p>NIR spectra are often pre-processed in order to remove systematic noise such as base-line variation and multiplicative scatter effects. This is done by differentiating the spectra to first or second derivatives, by Multiplicative Signal Correction (MSC), or by similar filtering methods. This pre-processing may, however, also remove information from the spectra regarding Y (the measured response variable in multivariate calibration applications). Provided is a variant of PLS that can be used to achieve a signal correction that is as close to orthogonal as possible to a given Y-vector or Y-matrix (430). Thus, ensuring that the signal correction removes as little information as possible regarding Y. In the case when the number of X-variables, in an X matrix, K exceeds the number of observations N, strict orthogonality is obtained. A filter (470) according to the present invention is named Orthogonal Signal Correction (OSC).</p> |
