Two-Sided Projection Methods for Nonlinear Model Order Reduction
Abstract
In this paper, we investigate a recently introduced approach for nonlinear model order reduction based on generalized moment matching. Using basic tensor calculus, we propose a computationally efficient way of computing reduced-order models. We further extend the idea of two-sided interpolation methods to this more general setting by employing the tensor structure of the Hessian. We investigate the use of oblique projections in order to preserve...
Paper Details
Title
Two-Sided Projection Methods for Nonlinear Model Order Reduction
Published Date
Mar 11, 2015
Volume
37
Issue
2
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