Abstract
In this paper, we present a new approach for model order reduction problems, with multiple inputs and multiple outputs, named: Adaptive Global Tangential Arnoldi Algorithm. This method is based on a generalization of the global Arnoldi algorithm. The selection of the shifts and the tangent directions are done with an adaptive procedure. We give some algebraic properties and present some numerical examples to show the effectiveness of the proposed algorithm.
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Oberwolfach model reduction benchmark collection 2003. http://www.imtek.de/simulation/benchmark.
Oberwolfach model reduction benchmark collection 2003. http://www.imtek.de/simulation/benchmark.
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Bentbib, A.H., Jbilou, K. & Kaouane, Y. A Computational Global Tangential Krylov Subspace Method for Model Reduction of Large-Scale MIMO Dynamical Systems. J Sci Comput 75, 1614–1632 (2018). https://doi.org/10.1007/s10915-017-0601-x
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DOI: https://doi.org/10.1007/s10915-017-0601-x