Evaluating Derivatives : Principles And Techniques Of Algorithmic Differentiation - Couverture souple

Griewank, Andreas

 
9780898714517: Evaluating Derivatives : Principles And Techniques Of Algorithmic Differentiation
Couverture souple
ISBN 10 : 0898714516 ISBN 13 : 9780898714517
Editeur : Society For Industrial And Applied Mathematics, 2000

Synopsis

Algorithmic, or automatic, differentiation (AD) is concerned with the accurate and efficient evaluation of derivatives for functions defined by computer programs. No truncation errors are incurred, and the resulting numerical derivative values can be used for all scientific computations that are based on linear, quadratic, or even higher order approximations to nonlinear scalar or vector functions. In particular, AD has been applied to optimization, parameter identification, equation solving, the numerical integration of differential equations, and combinations thereof. Apart from quantifying sensitivities numerically, AD techniques can also provide structural information, e.g., sparsity pattern and generic rank of Jacobian matrices.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Algorithmic, or automatic, differentiation (AD) is concerned with the accurate and efficient evaluation of derivatives for functions defined by computer programs. No truncation errors are incurred, and the resulting numerical derivative values can be used for all scientific computations that are based on linear, quadratic, or even higher order approximations to nonlinear scalar or vector functions. In particular, AD has been applied to optimization, parameter identification, equation solving, the numerical integration of differential equations, and combinations thereof. Apart from quantifying sensitivities numerically, AD techniques can also provide structural information, e.g., sparsity pattern and generic rank of Jacobian matrices.

Biographie de l'auteur

Andreas Griewank is a former senior scientist of Argonne National Laboratory and authored the first edition of this book in 2000. He holds a Ph.D. from the Australian National University and is currently Deputy Director of the Institute of Mathematics at Humboldt University Berlin and a member of the DFG Research Center Matheon, Mathematics for Key Technologies. His main research interests are nonlinear optimization and scientific computing.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Society For Industrial And Applied Mathematics
Date d'édition
2000
Langue
anglais
ISBN 10 
0898714516
ISBN 13 
9780898714517
Reliure
Broché
Nombre de pages
390
Coordonnées du fabricant
non disponible
Personne responsable
non disponible

Autres éditions populaires du même titre

9780898716597: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation

Edition présentée

ISBN 10 :  0898716594 ISBN 13 :  9780898716597
Editeur : Society for Industrial and Appli..., 2008
Couverture souple