This unique text blends together state estimation and chemometrics for the application of advanced data-processing techniques. State Estimation in Chemometrics, second edition describes the basic methods for chemical analysis—the multicomponent, calibration and titration systems—from a new perspective. It succinctly reviews the history of state estimation and chemometrics and provides examples of its many applications, including classical estimation, state estimation, nonlinear estimation, the multicomponent, calibration and titration systems and the Kalman filter. The concepts are introduced in a logical way and built up systematically to appeal to specialist post-graduates working in this area as well as professionals in other areas of chemistry and engineering. This new edition covers the latest research in chemometrics, appealing to readers in bio-engineering, food science, pharmacy, and the life sciences fostering cross-disciplinary research. - Features a new chapter surveying the most up-to-date scientific literature on chemometrics, highlighting developments that have occurred since the first edition published - Includes a new chapter devoted to new applications for state estimation in chemometrics - Covers a new chapter entirely devoted to subspace identification methods - Provides several new real-life examples of methods such as multiple modeling, principal component analysis, iterative target transformation factor analysis, and the generalized standard addition method
This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one of the most widely appearing problems in science, engineering, and business. In recent years this problem has gained importance due to the increasing availability of more sensitive sensors in science and engineering and due to the wide-spread use of computers in corporations which have increased the amount of time-series data collected by many magnitudes. An important feature of this book is the exploration of different approaches to handle and identify time dependent biomedical images. Biomedical imaging analysis and processing techniques deal with the interaction between all forms of radiation and biological molecules, cells or tissues, to visualize small particles and opaque objects, and to achieve the recognition of biomedical patterns. These are topics of great importance to biomedical science, biology, and medicine. Biomedical imaging analysis techniques can be applied in many different areas to solve existing problems. The various requirements arising from the process of resolving practical problems motivate and expedite the development of biomedical imaging analysis. This is a major reason for the fast growth of the discipline.
This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one of the most widely appearing problems in science, engineering, and business. In recent years this problem has gained importance due to the increasing availability of more sensitive sensors in science and engineering and due to the wide-spread use of computers in corporations which have increased the amount of time-series data collected by many magnitudes. An important feature of this book is the exploration of different approaches to handle and identify time dependent biomedical images. Biomedical imaging analysis and processing techniques deal with the interaction between all forms of radiation and biological molecules, cells or tissues, to visualize small particles and opaque objects, and to achieve the recognition of biomedical patterns. These are topics of great importance to biomedical science, biology, and medicine. Biomedical imaging analysis techniques can be applied in many different areas to solve existing problems. The various requirements arising from the process of resolving practical problems motivate and expedite the development of biomedical imaging analysis. This is a major reason for the fast growth of the discipline.
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