Automatic differentiation of algorithms

被引：141

作者：

Bartholomew-Biggs, M ^{[1
]}

Brown, S ^{[1
]}

Christianson, B ^{[1
]}

Dixon, L ^{[1
]}

机构：

[1] Univ Hertfordshire, Numer Optimisat Ctr, Hatfield AL10 9AB, Herts, England

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2000年 / 124卷 / 1-2期

关键词：

adjoint programming; algorithm; automatic differentiation; checkpoints; error analysis; function approximation; implicit equations; interval analysis; nonlinear optimization; optimal control; parallelism; penalty functions; program transformation; variable momentum;

D O I：

10.1016/S0377-0427(00)00422-2

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We introduce the basic notions of automatic differentiation, describe some extensions which are of interest in the context of nonlinear optimization and give some illustrative examples. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：171 / 190

页数：20

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