Model Based Parameter Estimation

Theory and Applications de

Éditeur :

Springer


Collection :

Contributions in Mathematical and Computational Sciences

Paru le : 2013-02-26

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Description

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.
Pages
334 pages
Collection
Contributions in Mathematical and Computational Sciences
Parution
2013-02-26
Marque
Springer
EAN papier
9783642303661
EAN EPUB
9783642303678

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
4649 Ko
Prix
94,94 €