| 摘要 |
Systems and methods are used to predict intensities of a saturated peak using a peak predictor. A set of data is selected from the plurality of intensity measurements that includes a saturated peak. Confidence values are assigned to each data point in the set of data producing a plurality of confidence value weighted data points. A peak predictor is selected. The peak predictor is applied to the plurality of confidence value weighted data points of the saturated peak producing predicted intensities for the saturated peak. The confidence values can include system confidence values, predictor confidence values, or a combination of system confidence values and predictor confidence values. The peak predictor can be a theoretical model, a dynamic model, an artificial neural network, or an analytical function representing a best fit of a plurality of probability density functions to a first set of measured data that includes a representative non-saturated peak.
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