Bibliothèque de L'IMIST/CNRST

Parameter Estimation and Optimum Experimental Design for Differential Equation Models: H.G. Bock, St. Körkel, J.P. Schlöder -- Adaptive Finite Element Methods for Parameter Identification Problems: B. Vexler -- Gauss-Newton Methods for Robust Parameter Estimation: T. Binder, E. Kostina -- An Optimal Scanning Sensor Activation Policy for Parameter Estimation of Distributed Systems: D. Ucínski -- Interaction between Experiment, Modeling and Simulation of Spatial Aspects in the JAK2/STAT5 Signaling Pathway: E. Friedmann, A. C. Pfeifer, R. Neumann, U. Klingmüller , R. Rannacher -- The Importance and Challenges of Bayesian Parameter Learning in Systems Biology: J. Mazur, L. Kaderali -- Experiment Setups and Parameter Estimation in Fluorescence Recovery After Photobleaching Experiments: A Review of Current Practice: J. Beaudouin, M. S. Mommer, H. G. Bock, R. Eils -- Drug Resistance in Infectious Diseases: Modeling, Parameter Estimation and Numerical Simulation: Le Thi Thanh An, W. Jäger -- Mathematical Models of Hematopoietic Reconstitution after Stem Cell Transplantation: A. Marciniak-Czochra, Th. Stiehl -- Combustion Chemistry and Parameter Estimation: M. Fischer, U. Riedel -- Numerical Simulation of Catalytic Reactors by Molecular-Based Models: O. Deutschmann, St. Tischer -- Model-Based Design of Experiments for Estimating Heat-Transport Parameters in Tubular Reactors: A.Badinski, D. Corbett -- Parameter Estimation for a Reconstructed SOFC Mixed-Conducting LSCF-Cathode: Th. Carraro, J. Joos -- An Application of Robust Parameter Estimation in Environmental Physics: G. Herzog, F. R. Vogel -- Parameter Estimation in Image Processing and Computer Vision: Ch. S. Garbe, B. Ommer.

This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The material chosen was presented at a multidisciplinary workshop on parameter estimation held in 2009 in Heidelberg. The contributions show how indispensable efficient methods of applied mathematics and computer-based modeling can be to enhancing the quality of interdisciplinary research.   The use of scientific computing to model, simulate, and optimize complex processes has become a standard methodology in many scientific fields, as well as in industry. Demonstrating that the use of state-of-the-art optimization techniques in a number of research areas has much potential for improvement, this book provides advanced numerical methods and the very latest results for the applications under consideration.