activity
20172023
most citedOn a variable step size modification of Hines' method in computational neuroscience

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

math.CA2023

Canonical Subspaces of Linear Time-Varying Differential-Algebraic Equations and Their Usefulness for Formulating Accurate Initial Conditions

Michael Hanke, Roswitha März

Accurate initial conditions have the task of precisely capturing and fixing the free integration constants of the flow considered. This is trivial for regular ordinary differential…

math.NA2022

On the sensitivity of implementations of a least-squares collocation method for linear higher-index differential-algebraic equations

Michael Hanke

The present paper continues our investigation of an implementation of a least-squares collocation method for higher-index differential-algebraic equations. In earlier papers, we we…

math.NA2020

Towards a reliable implementation of least-squares collocation for higher-index differential-algebraic equations

Michael Hanke, Roswitha März

In this note we discuss several questions concerning the implementation of overdetermined least-squares collocation methods for higher-index differential algebraic equations (DAEs)…

math.NA2019

Questions concerning differential-algebraic operators: Toward a reliable direct numerical treatment of differential-algebraic equations

Michael Hanke, Roswitha März

The nature of so-called differential-algebraic operators and their approximations is constitutive for the direct treatment of higher-index differential-algebraic equations. We trea…

math.NA2019

A least-squares collocation method for nonlinear higher-index differential-algebraic equations

Michael Hanke, Roswitha März

We introduce a direct numerical treatment of nonlinear higher-index differential-algebraic equations by means of overdetermined polynomial least-squares collocation. The procedure…

math.NA2017★ 1 cited

On a variable step size modification of Hines' method in computational neuroscience

Michael Hanke

For simulating large networks of neurons Hines proposed a method which uses extensively the structure of the arising systems of ordinary differential equations in order to obtain a…