Numerical derivatives and nonlinear analysis
Numerical derivatives and nonlinear analysis
Automation of nested matrix and derivative operations
Applied Mathematics and Computation
New computer methods for global optimization
New computer methods for global optimization
Applications of differentiation arithmetic
Reliability in computing: the role of interval methods in scientific computing
Automatic differentiation in C++
Journal of Object-Oriented Programming
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Simulated annealing: an initial application in econometrics
Computer Science in Economics and Management
Introduction to Maple
Global optimization using interval arithmetic
Computational Economics
Algorithm 737: INTLIB—a portable Fortran 77 interval standard-function library
ACM Transactions on Mathematical Software (TOMS)
Algorithm 746: PCOMP—a Fortran code for automatic differentiation
ACM Transactions on Mathematical Software (TOMS)
Algorithm 763: INTERVAL_ARITHMETIC: a Fortran 90 module for an interval data type
ACM Transactions on Mathematical Software (TOMS)
A simple automatic derivative evaluation program
Communications of the ACM
C++ Toolbox for Verified Scientific Computing I: Basic Numerical Problems
C++ Toolbox for Verified Scientific Computing I: Basic Numerical Problems
Automatic differentiation using almost any language
ACM SIGNUM Newsletter
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
| Hi-index | 0.00 |
Nonlinear estimation problems have a unknown number ofstationary points. Interval arithmetic is a promisingmethod that eliminates all but the global optimum.Automatic differentiation provides users with a convenientmethod of computing the gradient and Hessianof nonlinear functions. These two can be combined toprovide an efficient and convenient global optimizationprocess.