ADMIT-1 : Automatic Differentiation and MATLAB Interface Toolbox

Authors:
Thomas F. Coleman;Arun Verma
Affiliations:
-;-
Venue:
ADMIT-1 : Automatic Differentiation and MATLAB Interface Toolbox
Year:
1998

Citing 0
Cited 6

ADMIT-1: automatic differentiation and MATLAB interface toolbox

ACM Transactions on Mathematical Software (TOMS)
Jacobian code generated by source transformation and vertex elimination can be as efficient as hand-coding

ACM Transactions on Mathematical Software (TOMS)
Using AD to solve BVPs in MATLAB

ACM Transactions on Mathematical Software (TOMS)
An efficient overloaded implementation of forward mode automatic differentiation in MATLAB

ACM Transactions on Mathematical Software (TOMS)
Computation of normal form coefficients of cycle bifurcations of maps by algorithmic differentiation

Mathematics and Computers in Simulation
An efficient overloaded method for computing derivatives of mathematical functions in MATLAB

ACM Transactions on Mathematical Software (TOMS)

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Abstract

ADMIT-1 enables you to compute {\em sparse} Jacobian and Hessian matrices, using automatic differentiation technology, from a MATLAB environment. You need only supply a function to be differentiated and ADMIT-1 will exploit sparsity if present to yield sparse derivative matrices (in sparse MATLAB form). A generic AD tool, subject to some functionality requirements, can be plugged into ADMIT-1; examples include ADOL-C ~\cite{Griewank1996b} (C/C++ target functions) and ADMAT ~\cite{admat} (MATLAB target functions). ADMIT-1 also allows for the calculation of gradients and has several other related functions.