ISBN: 9781611974355 - automatic differentiation in matlab using admat with applications (17 risultati)

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Lingua: Inglese
Editore: Society for Industrial and Applied Mathematics, 2016
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Paperback. Condizione: New. The calculation of partial derivatives is a fundamental need in scientific computing. Automatic differentiation (AD) can be applied straightforwardly to obtain all necessary partial derivatives (usually first and, possibly, second derivatives) regardless of a code's complexity. However, the space and time efficiency of AD can be dramatically improved - sometimes transforming a problem from intractable to highly feasible - if inherent problem structure is used to apply AD in a judicious manner.This book discusses the efficient use of AD to solve real problems, especially multidimensional zero-finding and optimization, in the MATLAB environment. This book is concerned with the determination of the first and second derivatives in the context of solving scientific computing problems with an emphasis on optimization and solutions to nonlinear systems. The authors focus on the application rather than the implementation of AD, solve real nonlinear problems with high performance by exploiting the problem structure in the application of AD, and provide many easy to understand applications, examples, and MATLAB templates.…

Lingua: Inglese
Editore: Society for Industrial and Applied Mathematics, 2016
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Lingua: Inglese
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Lingua: Inglese
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Lingua: Inglese
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Lingua: Inglese
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Lingua: Inglese
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Condizione: New. In English.

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Kartoniert / Broschiert. Condizione: New. Über den AutorThomas F. Coleman is a Professor in the Department of Combinatorics and Optimization, as well as the Ophelia Lazaridis University Research Chair, at the University of Waterloo. He is also the Director of WatRISQ, an in.

Lingua: Inglese
Editore: Society For Industrial And Applied Mathematics (SIAM) Okt 2016, 2016
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Taschenbuch. Condizione: Neu. Neuware - The calculation of partial derivatives is a fundamental need in scientific computing. Automatic differentiation (AD) can be applied straightforwardly to obtain all necessary partial derivatives (usually first and, possibly, second derivatives) regardless of a code's complexity. However, the space and time efficiency of AD can be dramatically improved - sometimes transforming a problem from intractable to highly feasible - if inherent problem structure is used to apply AD in a judicious manner.This book discusses the efficient use of AD to solve real problems, especially multidimensional zero-finding and optimization, in the MATLAB environment. This book is concerned with the determination of the first and second derivatives in the context of solving scientific computing problems with an emphasis on optimization and solutions to nonlinear systems. The authors focus on the application rather than the implementation of AD, solve real nonlinear problems with high performance by exploiting the problem structure in the application of AD, and provide many easy to understand applications, examples, and MATLAB templates.…

Lingua: Inglese
Editore: Society for Industrial and Applied Mathematics, 2016
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Lingua: Inglese
Editore: Society for Industrial and Applied Mathematics,U.S., US, 2016
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Paperback. Condizione: New. The calculation of partial derivatives is a fundamental need in scientific computing. Automatic differentiation (AD) can be applied straightforwardly to obtain all necessary partial derivatives (usually first and, possibly, second derivatives) regardless of a code's complexity. However, the space and time efficiency of AD can be dramatically improved - sometimes transforming a problem from intractable to highly feasible - if inherent problem structure is used to apply AD in a judicious manner.This book discusses the efficient use of AD to solve real problems, especially multidimensional zero-finding and optimization, in the MATLAB environment. This book is concerned with the determination of the first and second derivatives in the context of solving scientific computing problems with an emphasis on optimization and solutions to nonlinear systems. The authors focus on the application rather than the implementation of AD, solve real nonlinear problems with high performance by exploiting the problem structure in the application of AD, and provide many easy to understand applications, examples, and MATLAB templates.…