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Computing Derivatives

  • Guy ChaventEmail author
Chapter
  • 2k Downloads
Part of the Scientific Computation book series (SCIENTCOMP)

Abstract

We address in this chapter a practical aspect of the numerical resolution of NLS problems, namely the computation of the gradient of the objective function or the Jacobian of the forward map, after discretization has occurred. This calculation has to be computed both accurately, so that the optimization algorithm has a chance to work properly, and efficiently, in order to keep computation time as low as possible.

Keywords

State Equation Sensitivity Function Adjoint Equation Observation Operator Adjoint State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Ceremade, Université Paris-DauphineParis Cedex 16France
  2. 2.Inria-RocquencourtLe Chesnay CedexFrance

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