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An alternative method to that presented in the first paper of the series for improving the resolution of spectrophotometric measurements via processing of spectrometric data is proposed. It is based on the approximation of the solution with a spline function the parameters of which are determined by means of a recursive Kalman-filter-based algorithm. It is assumed in the paper that the model of the spectrophotometric data has the form of an integral, convolution-type equation of the first kind. It is shown, using synthetic and real-world spectrophotometric data, that the proposed method allows for significant reduction of computational requirements as well as an improvement in the quality of correction.
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Slima et al. (1997) studied this question.
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