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Automatic differentiation in MATLAB using ADMAT with applications / Thomas F. Coleman, University of Waterloo, Waterloo, Ontario, Canada, Wei Xu, Tongji University, Shanghai, P.R. China and Global Risk Institute, Toronto, Canada

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Software, environments, and tools ; 27Publisher: Philadelphia : SIAM, Society for Industrial and Applied Mathematics, [2016], [2016]Description: 1 Online-Ressource (XI, 105 Seiten)ISBN:
  • 9781611974362
Subject(s): Additional physical formats: 9781611974355 | Erscheint auch als: Automatic differentiation in MATLAB using ADMAT with applications. Druck-Ausgabe Philadelphia : siam, Society for Industrial and Applied Mathematics, 2016. xi, 105 SeitenDDC classification:
  • 518/.53028553 23
MSC: MSC: *65D25 | 65-01 | 68W30 | 91G60DOI: DOI: 10.1137/1.9781611974362Online resources: Summary: 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. Automatic Differentiation in MATLAB Using ADMAT with Applications discusses the efficient use of AD to solve real problems, especially multidimensional zero-finding and optimization, in the MATLAB{reg} 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.PPN: PPN: 865675465Package identifier: Produktsigel: ZDB-72-SIA
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