Rosenbrock methods
Encyclopedia
Rosenbrock methods may refer to either of two distinct ideas in numerical computation, both named for Howard H. Rosenbrock
. Rosenbrock optimization methods are a family of numerical optimization algorithms applicable to optimization problems in which the objective function is inexpensive to compute yet and the explicit derivative cannot be computed efficiently. Rosenbrock methods for stiff differential equations
are methods for solving ordinary differential equations
that contain a wide range of characteristic timescales.
Rosenbrock optimization methods are related to Nelder-Mead method
s, but with better convergence properties.
Howard Harry Rosenbrock
Howard Harry Rosenbrock was a leading figure in control theory and control engineering. He was born in Ilford, England in 1920, graduated in 1941 from University College London with a 1st class honors degree in Electrical Engineering. He served in the Royal Air Force during World War II. He...
. Rosenbrock optimization methods are a family of numerical optimization algorithms applicable to optimization problems in which the objective function is inexpensive to compute yet and the explicit derivative cannot be computed efficiently. Rosenbrock methods for stiff differential equations
Stiff equation
In mathematics, a stiff equation is a differential equation for which certain numerical methods for solving the equation are numerically unstable, unless the step size is taken to be extremely small. It has proved difficult to formulate a precise definition of stiffness, but the main idea is that...
are methods for solving ordinary differential equations
Ordinary differential equation
In mathematics, an ordinary differential equation is a relation that contains functions of only one independent variable, and one or more of their derivatives with respect to that variable....
that contain a wide range of characteristic timescales.
Rosenbrock optimization methods are related to Nelder-Mead method
Nelder-Mead method
The Nelder–Mead method or downhill simplex method or amoeba method is a commonly used nonlinear optimization technique, which is a well-defined numerical method for twice differentiable and unimodal problems...
s, but with better convergence properties.