Suchergebnisse - Beyn, Wolf-Jürgen

Invariant manifolds for non-autonomous systems with application to one-step methods

von Zou, Y.-K, Beyn, Wolf-Jürgen

On smothness and invariance properties of the Gauss-Newton method

von Beyn, Wolf-Jürgen

Numerical approximation of homoclinic chaos

von Beyn, Wolf-Jürgen, Kleinkauf, Jan-Martin

The numerical computation of homoclinic orbits for maps

von Beyn, Wolf-Jürgen, Kleinkauf, Jan-Martin

Modelling memory functions with recurrent neural networks consisting of input compensation units

Band 1 - Static situations

von Kühn, Simone, Beyn, Wolf-Jürgen, Cruse, Holk 1942-

Computing center manifolds for a discretized infinite dimensional Hamiltonian system: a case study

von Du, Wei-Hua, Beyn, Wolf-Jürgen, Huang, Mingyou

Stability of traveling waves: dichotomies and eigenvalue conditions on finite intervals

von Beyn, Wolf-Jürgen, Lorenz, Jens 1949-

A dynamical model of the leech

von Alscher, Christian, Beyn, Wolf-Jürgen

Numerical analysis of stochastic processes

von Beyn, Wolf-Jürgen, Kruse, Raphael 1983-

A note on symbolic dynamics near connecting orbits of maps

von Beyn, Wolf-Jürgen

Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data

von Beyn, Wolf-Jürgen, Garay, Barnabas M.

Connecting paracontractivity and convergence of products

von Beyn, Wolf-Jürgen, Elsner, Ludwig 1939-

Numerical analysis of stochastic processes

von Beyn, Wolf-Jürgen, Kruse, Raphael 1983-

Modelling memory functions with recurrent neural networks consisting of input compensation units

Band 2 - Dynamic situations

von Kühn, Simone, Beyn, Wolf-Jürgen, Cruse, Holk 1942-

A basic mathematical model for iron uptake in bacteria

von Beyn, Wolf-Jürgen, Rieger, Janosch

Runge-Kutta discretizations of singularly perturbed gradient equations

von Beyn, Wolf-Jürgen, Schropp, Johannes

Stability and paracontractivity of discrete linear inclusions

von Vladimirov, Aleksandr A., Elsner, Ludwig 1939-, Beyn, Wolf-Jürgen

Modelling memory functions with recurrent neural networks consisting of input compensation units

von Kühn, Simone, Beyn, Wolf-Jürgen, Cruse, Holk 1942-