Start » Next »
Abstract
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.
Start » Next »