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Comparison of a neural network with multiple linear regression for quantitative analysis in ICP-atomic emission spectroscopy

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Summary

A two layer perceptron with backpropagation of error is used for quantitative analysis in ICP-AES. The network was trained by emission spectra of two interfering lines of Cd and As and the concentrations of both elements were subsequently estimated from mixture spectra. The spectra of the Cd and As lines were also used to perform multiple linear regression (MLR) via the calculation of the pseudoinverse S+ of the sensitivity matrix S. In the present paper it is shown that there exist close relations between the operation of the perceptron and the MLR procedure. These are most clearly apparent in the correlation between the weights of the backpropagation network and the elements of the pseudoinverse. Using MLR, the confidence intervals over the predictions are exploited to correct for the optical device of the wavelength shift.

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Schierle, C., Otto, M. Comparison of a neural network with multiple linear regression for quantitative analysis in ICP-atomic emission spectroscopy. Fresenius J Anal Chem 344, 190–194 (1992). https://doi.org/10.1007/BF00322708

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  • DOI: https://doi.org/10.1007/BF00322708

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