Aspects of application of Kalman filtering in multicomponent spectrophotometry.
It is shown theoretically and experimentally that the reliability of the analytical results obtained by Kalman filtering in multicomponent spectrophotometry can be judged by means of the normalized autocorrelation coefficient (NAC) of the innovation sequence. Variations of the initial values of the concentration vector X(0), the error covariance matrix P(0), and the measurement noise variance R over a wide range do not show a substantial effect on the computed results. The effect of the rounding-off errors associated with application of different forms of the equation for calculation of the error covariance matrix is also discussed.
Liu
Y M
YM
Department of Chemistry and Chemical Engineering, Hunan University, Changsha, People's Republic of China.
Yu
R Q
RQ