文件名称:
User Guide for Mad - a Matlab Automatic Differentiation Toolbox TOMLAB /MAD
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文件大小: 493kb
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上传时间: 2013-12-27
详细说明： Mad is a Matlab library of functions and utilities for the automatic differentiation of Matlab functions/ statements via operator and function overloading. Currently the forward mode of automatic differentiation is supported via the fmad class. For a single directional derivative objects of the fmad class use Matlab arrays of the same size for a variable’s value and its directional derivative. Multiple directional derivatives are stored in objects of the derivvec class allowing for an internal 2-D, matrix storage so allowing the use of sparse matrix storage for derivatives and ensuring efficient linear combination of derivative vectors via high-level Matlab functions. This user guide covers: • installation of Mad on UNIX and PC platforms, • using TOMLAB /MAD, • basic use of the forward mode for differentiating expressions and functions • advanced use of the forward mode including: – dynamic propagation of sparse derivatives, – sparse derivatives via compression, – differentiating implicitly defined functions, – control of dependencies, • use of high-level interfaces for solving ODEs and optimization problems outside of the TOMLAB framework, • differentiating black-box functions for which derivatives are known. ...展开收缩
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