Automatic Differentiation: Applications, Theory, and Implementations: Applications, Theory and Implementations

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English | 388 pages | Springer; 2006th edition (December 14, 2005) | 3540284036 | PDF | 12.93 MbThis collection covers the state of the art in automatic differentiation theory and practice. Practitioners and students will learn about advances in automatic differentiation techniques and strategies for the implementation of robust and powerful tools. Computational scientists and engineers will benefit from the discussion of applications, which provide insight into effective strategies for using automatic differentiation for design optimization, sensitivity analysis, and uncertainty quantification.

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