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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.
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Previews available in: English
Subjects
Differential equations, Numerical analysis, Ordinary Differential Equations, Calculus of Variations and Optimal Control; Optimization, Partial Differential equations, Mathematical Modeling and Industrial Mathematics, Mathematics, Mathematical optimization, Computational Science and Engineering, Computer scienceEdition | Availability |
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1
Model Based Parameter Estimation: Theory and Applications
Mar 06, 2015, Springer
paperback
3642440762 9783642440762
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2
Model Based Parameter Estimation: Theory and Applications
Feb 26, 2013, Springer
paperback
3642303684 9783642303685
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3
Model Based Parameter Estimation: Theory and Applications
2013, Springer Berlin Heidelberg, Imprint: Springer
electronic resource :
in English
3642303676 9783642303678
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Source title: Model Based Parameter Estimation: Theory and Applications
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