Automatic Differentiation in MATLAB Using ADMAT with Applications
Thomas F. Coleman, Cornell University;
Wei Xu, Huazhong University of Science and Technology
SIAM, 2016
ISBN: 978-1-611974-35-5;
Language: English
Automatic Differentiation in MATLAB Using ADMAT with Applications discusses the efficient use of automatic differentiation (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. Optimization Toolbox is also used in some examples.
This book will prove useful to financial engineers, quantitative analysts, and researchers working with inverse problems, as well as to engineers and applied scientists in other fields.
