PARALLEL KALMAN FILTERS FOR PEAK PURITY ANALYSIS - EXTENSIONS TO NONIDEAL DETECTOR RESPONSE

A mathematical method for detecting spectral impurities in liquid chro matographic peaks measured with a diode array detector (LC-DAD) is des cribed. The new method compensates for certain measurement non-idealit ies, minimizing the likelihood of a false indication of an impurity. T he algorithm, evolving projection analysis, is based on a previously r eported method in which points in an n-dimensional absorbance space (n = number of wavelengths) are projected onto two-dimensional subspaces and modeled using the Kalman filter. Model deviations can be indicati ve of the presence of spectral impurities, or may result from measurem ent artifacts such as heteroscedastic noise or non-linear detector res ponse. The modified algorithm incorporates model variants that mask th e effects of heteroscedastic noise and non-linearities so that impurit ies can be detected even in the presence of these artifacts. A noise m odel is developed for the DAD and simulations are used to evaluate the modified algorithm. Simulations are validated through the use of expe rimental data. It is demonstrated that, except in cases where the effe cts of non-linearities become severe, the modified model successfully compensates for these measurement non-idealities.