Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation by Andreas Griewank
Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation (Frontiers in Applied Mathematics) by Andreas Griewank
English | Jan 1, 1987 | ISBN: 0898714516 | 394 Pages | PDF | 20 MB
English | Jan 1, 1987 | ISBN: 0898714516 | 394 Pages | PDF | 20 MB
Algorithmic, or automatic, differentiation (AD) is concerned with the accurate and efficient evaluation of derivatives for functions defined by computer programs. No truncation errors are incurred, and the resulting numerical derivative values can be used for all scientific computations that are based on linear, quadratic, or even higher order approximations to nonlinear scalar or vector functions