Add to ORKGAbstract. Krylov subspace methods have become very popular, not only for solving large scale linear systems, but also in the area of model order reduction. It is also well known that the performance of iterative solution techniques depends crucially on the choice of preconditioning matrix. Within the area of model order reduction, the concept of preconditioning has not yet been introduced. However, recent reduction problems arising in electronics applications clearly demonstrate the need for some kind of preconditioning step prior to the actual model order reduction. In this paper, we present initial ideas and some test results.
Abstract. Incomplete factorization preconditioners such as ILU, ILUT and MILU are well-known robust ...
This thesis focuses on the model reduction of linear systems and the solution of large scale linear ...
In this work we investigate the application of some model order reduction techniques, based on Krylo...
Abstract. Krylov subspace methods have become very popular, not only for solving large scale linear ...
Krylov subspace methods have become very popular, not only for solving large scale linear systems, b...
Due to the decreasing sizes of electrical devices used nowadays and the increasing frequency, the in...
New variants of Krylov subspace methods for numerical solution of linear systems, eigenvalue, and mo...
Numerical experiments are presented whereby the effect of reorderings on the convergence of precondi...
Efficient solution of sequences of linear systems is a task arising in numerous applications in engi...
When simulating a mechanism from science or engineering, or an industrial process, one is frequently...
This chapter offers an introduction to Model Order Reduction (MOR). It gives an overview on the meth...
Complex dynamic linear systems of equations are solved by numerical iterative methods, which need mu...
AbstractThe simulation of electronic circuits involves the numerical solution of very large-scale, s...
This chapter offers an introduction to Model Order Reduction (MOR). It gives an overview on the meth...
In this paper we consider the parameter dependent class of preconditioners M#ℎ(a, delta,D) defined i...
Abstract. Incomplete factorization preconditioners such as ILU, ILUT and MILU are well-known robust ...
This thesis focuses on the model reduction of linear systems and the solution of large scale linear ...
In this work we investigate the application of some model order reduction techniques, based on Krylo...
Abstract. Krylov subspace methods have become very popular, not only for solving large scale linear ...
Krylov subspace methods have become very popular, not only for solving large scale linear systems, b...
Due to the decreasing sizes of electrical devices used nowadays and the increasing frequency, the in...
New variants of Krylov subspace methods for numerical solution of linear systems, eigenvalue, and mo...
Numerical experiments are presented whereby the effect of reorderings on the convergence of precondi...
Efficient solution of sequences of linear systems is a task arising in numerous applications in engi...
When simulating a mechanism from science or engineering, or an industrial process, one is frequently...
This chapter offers an introduction to Model Order Reduction (MOR). It gives an overview on the meth...
Complex dynamic linear systems of equations are solved by numerical iterative methods, which need mu...
AbstractThe simulation of electronic circuits involves the numerical solution of very large-scale, s...
This chapter offers an introduction to Model Order Reduction (MOR). It gives an overview on the meth...
In this paper we consider the parameter dependent class of preconditioners M#ℎ(a, delta,D) defined i...
Abstract. Incomplete factorization preconditioners such as ILU, ILUT and MILU are well-known robust ...
This thesis focuses on the model reduction of linear systems and the solution of large scale linear ...
In this work we investigate the application of some model order reduction techniques, based on Krylo...