Nonnodal Condensation of Eigenvalue Problems

We generalize the Guyan condensation of large symmetric eigenvalue problems to allow general degrees of freedom to be maste r variables. On one hand useful information from other condensation methods (such as Component Mode Synthesis) thus can be incorporated into the method. On the other hand this opens the way to iterative refinement of eigen-vector approximations. Convergence of such a procedure follows from the result, that one step of (static) condensation is equivalent to one step of inverse subspace iteration. A short outlook on several applications is included.

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