Approximate implicit subspace iteration with alternating directions for LTI system model reduction

We propose an Approximate Implicit Subspace Iteration with Alternating Directions (AISIAD) framework for Linear Time Invariant (LTI) system model reduction. Within this framework, dominant eigensubspaces of the product of the system Gramians are approximated directly. This has advantage over approaches that consider the system Gramians separately. We construct two methods within the framework, one uses the QR updates, the other uses the SVD updates. Numerical results show the efficiency of the proposed methods. Copyright c © 2006 John Wiley & Sons, Ltd.