9783540689355
Advances In Automatic Differentiation (Lecture Notes In Computational Science And Engineering)
Springer (2008)
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#492

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This collection covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization.

Product Details
LoC Classification QA304.I58 2006
Dewey 515.330285
Format Paperback
Cover Price 129,00 €
No. of Pages 370
Height x Width 234 x 156 mm
Personal Details
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