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This unique text blends together state estimation and chemometrics for the application of advanced data-processing techniques. It further applies system theory in order to develop a modular framework to be implemented on computers for the development of simple intelligent analyzers. Short reviews on the history of state estimation and chemometrics are given, together with examples of the applications described, including classical estimation, state estimation, non-linear estimation, the multi-component, calibration and titration systems, and the Kalman filter. The contents are very systematic and logically build upon the ideas, making this book appealing to specialist post-graduates working in this area, along with professionals in other areas of chemistry and engineering. Contents: Introduction u Classical Estimation Linear Model; Least Squares; Curve-Fitting; Recursive Approach; Examples --- State Estimation State Space Model; Intermezzo; Prediction; Filtering; Kalman Filter; Smo
List of contents
Introduction; Classical estimation; State estimation; Statistics; Non-linear estimation; The multi-component system; The calibration system; The titration system; Multiple modelling; Principal components; Appendix: Matrix fundamentals; Bibliography and index.
About the author
Dr. Pierre Cornelis Thijssen studied chemistry at the Radboud University in the Netherlands, obtaining his Masters Degree in 1978. He then moved to the University of Amsterdam, where he graduated in 1986 with a Ph.D based on his thesis entitled "State Estimation in Chemometrics" which is the basis of this book. Since then, Dr Thijssen has worked for various companies as a laboratory manager and chemometrician.
