Evaluating Derivatives: Principles , 2 Ed

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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, 2 Ed
Society for Industrial and Applied Mathematic | 2008 | ISBN: 0898716594 | 460 pages | PDF | 3,3 MB




                                                                                               
http://depositfiles.com/files/qbv4poy1v                                                

                                                                                                
http://www.filefactory.com/file/ah57b8h/n/0898714516derivat_rar                                                

Algorithmic, or automatic, differentiation (AD) is a growing area of theoretical research and software development concerned with the accurate and efficient evaluation of derivatives for function evaluations given as computer programs. The resulting derivative values are useful for all scientific computations that are based on linear, quadratic, or higher order approximations to nonlinear scalar or vector functions.
AD has been applied in particular to optimization, parameter identification, nonlinear equation solving, the numerical integration of differential equations, and combinations of these. Apart from quantifying sensitivities numerically, AD also yields structural dependence information, such as the sparsity pattern and generic rank of Jacobian matrices. The field opens up an exciting opportunity to develop new algorithms that reflect the true cost of accuratederivatives and to use them for improvements in speed and reliability.
This second edition has been updated and expanded to cover recent developments in applications and theory, including an elegant NP completeness argument by Uwe Naumann and a brief introduction to scarcity, a generalization of sparsity. There is also added material on checkpointing and iterative differentiation. To improve readability the more detailed analysis of memory and complexity bounds has been relegated to separate, optional chapters.The book consists of three parts: a stand-aloneintroduction to the fundamentals of AD and its software; a thorough treatment of methods for sparse problems; and final chapters on program-reversal schedules, higherderivatives, nonsmooth problems and iterative processes. Each of the 15 chapters concludes with examples and exercises.
Audience: This volume will be valuable to designers of algorithms and software for nonlinear computational problems. Current numerical software users should gain the insight necessary to choose and deploy existing AD software tools to the best advantage. Contents: Rules; Preface; Prologue; Mathematical Symbols; Chapter 1: Introduction; Chapter 2: A Framework for Evaluating Functions; Chapter 3: Fundamentals of Forward and Reverse; Chapter 4: Memory Issues and Complexity Bounds; Chapter 5: Repeating and Extending Reverse; Chapter 6: Implementation and Software; Chapter 7: Sparse Forward and Reverse; Chapter 8: Exploiting Sparsity by Compression; Chapter 9: Going beyond Forward and Reverse; Chapter 10: Jacobian and Hessian Accumulation; Chapter 11: Observations on Efficiency; Chapter 12: Reversal Schedules and Checkpointing; Chapter 13: Taylor and Tensor Coefficients; Chapter 14:Differentiation without Differentiability; Chapter 15: Implicit and Iterative Differentiation ; Epilogue; List of Figures; List of Tables; Assumptions and Definitions; Propositions, Corollaries, and Lemmas; Bibliography; Index

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关键词：derivatives Principles Derivative Evaluating principle derivatives Principles Evaluating

thanks for sharing this

好东西啊，哈哈

楼主从那找到的啊？

好东西，学习了！！！

deposite的不能下，filefactory是第一版，坛子里面的附件也是第一版。

hittiger 发表于 2010-4-8 15:30
deposite的不能下，filefactory是第一版，坛子里面的附件也是第一版。

没错，是的。

Thanks a lot

Thank you for sharing - this is a very difficult subject.

这都是第一版，为什么标个2nd ！！！！！
楼主搞到第二版了吗？