Optimization based model order reduction for stochastic systems

نویسندگان

چکیده

In this paper, we bring together the worlds of model order reduction for stochastic linear systems and H2-optimal deterministic systems. particular, supplement complete theory error bounds differential equations. With these bounds, establish a link between output (with additive multiplicative noise) modified versions H2-norm both bilinear When deriving respective optimality conditions minimizing see that techniques related to iterative rational Krylov algorithms (IRKA) are very natural effective methods reducing dimension large-scale with and/or noise. We apply (linear bilinear) IRKA show their efficiency in numerical experiments.

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ژورنال

عنوان ژورنال: Applied Mathematics and Computation

سال: 2021

ISSN: ['1873-5649', '0096-3003']

DOI: https://doi.org/10.1016/j.amc.2020.125783