| USE OF THE KALMAN FILTER FOR MULTIVARIATE CALIBRATION IN A REAL SYSTEM AND ITS COMPARISON WITH CLS AND PURE COMPONENT CALIBRATION METHODS |
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| 作者姓名： | L. V. PEREZ-ARRIBAS F. NAVARRO-VILLOSLADA M. E. LEON-GONZALEA L. M. POLO-DIEZ Departamento de Quimica Analiti Facultad de Ciencias Quimicas Universidad Complutense E- Madri Spain |
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| 作者单位： | L. V. PEREZ-ARRIBAS;F. NAVARRO-VILLOSLADA;M. E. LEON-GONZALEA;L. M. POLO-DIEZ，Departamento de Quimica Analitica，Facultad de Ciencias Quimicas，Universidad Complutense，E-28040 Madrid，Spain |
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| 摘 要： | The usefulness of the Kalman filter as an algorithm for calibration in a real system is shown. Results arecompared with classical least squares and pure component calibration. The prediction of four prioritypollutant chlorophenols in binary, ternary and quaternary mixtures was also carried out by Kalmanfiltering. The condition number, standard deviation and prediction error have been employed to choosethe most suitable wavelength range. Comparison of the standard error of prediction in the validation setshows significant differences between the evaluated chlorophenols, the best results being obtained withKalman multivariate calibration.
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USE OF THE KALMAN FILTER FOR MULTIVARIATE CALIBRATION IN A REAL SYSTEM AND ITS COMPARISON WITH CLS AND PURE COMPONENT CALIBRATION METHODS |
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| L. V. PEREZ-ARRIBAS,F. NAVARRO-VILLOSLADA,M. E. LEON-GONZALEA,L. M. POLO-DIEZ,Departamento de Quimica Analiti,Facultad de Ciencias Quimicas,Universidad Complutense,E- Madri,Spain.USE OF THE KALMAN FILTER FOR MULTIVARIATE CALIBRATION IN A REAL SYSTEM AND ITS COMPARISON WITH CLS AND PURE COMPONENT CALIBRATION METHODS[J].Journal of Geographical Sciences,1993(4). |
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| Authors: | L V PEREZ-ARRIBAS F NAVARRO-VILLOSLADA M E LEON-GONZALEA L M POLO-DIEZ Departamento de Quimica Analitic Facultad de Ciencias Quimicas Universidad Complutense E- Madri Spain |
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| Abstract: | The usefulness of the Kalman filter as an algorithm for calibration in a real system is shown. Results are compared with classical least squares and pure component calibration. The prediction of four priority pollutant chlorophenols in binary, ternary and quaternary mixtures was also carried out by Kalman filtering. The condition number, standard deviation and prediction error have been employed to choose the most suitable wavelength range. Comparison of the standard error of prediction in the validation set shows significant differences between the evaluated chlorophenols, the best results being obtained with Kalman multivariate calibration. |
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| Keywords: | Kalman filter Multivariate calibration Condition number Prediction error |
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