Residual norm estimates are derived for a general class of methods based on projection techniques on subspaces of the form K m + W, where K m is the standard Krylov subspace associated with the original linear system, and W is some other subspace. Thesèaugmented Krylov subspace methods' include eigenvalue deeation techniques as well as block-Krylov methods. Residual bounds are established which...

Moment matching theorems for Krylov subspace based model reduction of higherorder linear dynamical systems are presented in the context of higher-order Krylov subspaces. We introduce the definition of a nth-order Krylov subspace Kn k ({Ai} n i=1;u) based on a sequence of n square matrices {Ai}i=1 and vector u. This subspace is a generalization of Krylov subspaces for higher-order systems, incor...

Many different techniques to reduce the dimensions of a model have been proposed in the near past. Krylov subspace methods are relatively cheap, but generate non-optimal models. In this paper a combination of Krylov subspace methods and Orthonormal Vector Fitting is proposed. In that way an optimal model for a large model can be generated. In the first step, a Krylov subspace method reduces the...