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Model Based Parameter Estimation

Theory and Applications

  • Book
  • © 2013

Overview

Editors:
  1. Hans Georg Bock

    1. Interdisciplinary Center for Scientific, Computing (IWR), Heidelberg University, Heidelberg, Germany

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  2. Thomas Carraro

    1. Institute for Applied Mathematics, Heidelberg University, Heidelberg, Germany

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  3. Willi Jäger

    1. Interdisciplinary Center for Scientific, Computing (IWR), Heidelberg University, Heidelberg, Germany

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  4. Stefan Körkel

    1. Interdisciplinary Center for, Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany

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  5. Rolf Rannacher

    1. Institute for Applied Mathematics, Heidelberg University, Heidelberg, Germany

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  6. Johannes P. Schlöder

    1. Interdisciplinary Center for Scientific, Computing (IWR), Heidelberg University, Heidelberg, Germany

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  • Overview of state-of-the-art methods for model based parameter estimation
  • Applications for several scientific disciplines: biology, medicine, chemistry, electrochemistry, environmental physics, image processing and computer vision
  • Parameter estimation is a key feature of computational modelling ?
  • Includes supplementary material: sn.pub/extras

Part of the book series: Contributions in Mathematical and Computational Sciences (CMCS, volume 4)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Parameter Estimation and Optimum Experimental Design for Differential Equation Models

    • Hans Georg Bock, Stefan Körkel, Johannes P. Schlöder
    Pages 1-30

  3. Adaptive Finite Element Methods for Parameter Identification Problems

    • Boris Vexler
    Pages 31-54

  4. Gauss–Newton Methods for Robust Parameter Estimation

    • Tanja Binder, Ekaterina Kostina
    Pages 55-87

  5. An Optimal Scanning Sensor Activation Policy for Parameter Estimation of Distributed Systems

    • Dariusz Uciński
    Pages 89-124

  6. Interaction Between Experiment, Modeling and Simulation of Spatial Aspects in the JAK2/STAT5 Signaling Pathway

    • Elfriede Friedmann, Andrea C. Pfeifer, Rebecca Neumann, Ursula Klingmüller, Rolf Rannacher
    Pages 125-143

  7. The Importance and Challenges of Bayesian Parameter Learning in Systems Biology

    • Johanna Mazur, Lars Kaderali
    Pages 145-156

  8. Experiment Setups and Parameter Estimation in Fluorescence Recovery After Photobleaching Experiments: A Review of Current Practice

    • J. Beaudouin, Mario S. Mommer, Hans Georg Bock, Roland Eils
    Pages 157-169

  9. Drug Resistance in Infectious Diseases: Modeling, Parameter Estimation and Numerical Simulation

    • Le Thi Thanh An, Willi Jäger
    Pages 171-190

  10. Mathematical Models of Hematopoietic Reconstitution After Stem Cell Transplantation

    • Anna Marciniak-Czochra, Thomas Stiehl
    Pages 191-206

  11. Combustion Chemistry and Parameter Estimation

    • Marc Fischer, Uwe Riedel
    Pages 207-226

  12. Numerical Simulation of Catalytic Reactors by Molecular-Based Models

    • Olaf Deutschmann, Steffen Tischer
    Pages 227-250

  13. Model-Based Design of Experiments for Estimating Heat-Transport Parameters in Tubular Reactors

    • Alexander Badinski, Daniel Corbett
    Pages 251-266

  14. Parameter Estimation for a Reconstructed SOFC Mixed-Conducting LSCF-Cathode

    • Thomas Carraro, Jochen Joos
    Pages 267-285

  15. An Application of Robust Parameter Estimation in Environmental Physics

    • Alexandra G. Herzog, Felix R. Vogel
    Pages 287-309

  16. Parameter Estimation in Image Processing and Computer Vision

    • Christoph S. Garbe, Björn Ommer
    Pages 311-334
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Keywords

About this book

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.

Editors and Affiliations

  • Interdisciplinary Center for Scientific, Computing (IWR), Heidelberg University, Heidelberg, Germany

    Hans Georg Bock, Willi Jäger, Johannes P. Schlöder

  • Institute for Applied Mathematics, Heidelberg University, Heidelberg, Germany

    Thomas Carraro, Rolf Rannacher

  • Interdisciplinary Center for, Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany

    Stefan Körkel

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