We use the theoretical framework of General Linear Methods (GLMs) to analyze and generalize the class of Cash’s Modified Extended Backward Differentiation Formulae (MEBDF). Keeping the structure of MEBDF and their computational cost we propose a more general class of methods that can be viewed as a composition of modified linear multistep methods. These new methods are characterized by smaller error constants and possibly larger angles of A(α)-stability. Numerical experiments which confirm the good performance of these methods on a set of stiff problems are also reported.

Composition of Linear Multistep Methods

IZZO, GIUSEPPE;
2015

Abstract

We use the theoretical framework of General Linear Methods (GLMs) to analyze and generalize the class of Cash’s Modified Extended Backward Differentiation Formulae (MEBDF). Keeping the structure of MEBDF and their computational cost we propose a more general class of methods that can be viewed as a composition of modified linear multistep methods. These new methods are characterized by smaller error constants and possibly larger angles of A(α)-stability. Numerical experiments which confirm the good performance of these methods on a set of stiff problems are also reported.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/659536
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