Results 41 to 50 of about 4,793,633 (336)
Interpolation-based parameterized model order reduction of delayed systems [PDF]
, 2012 Three-dimensional electromagnetic methods are fundamental tools for the analysis and design of high-speed systems. These methods often generate large systems of equations, and model order reduction (MOR) methods are used to reduce such a high complexity.
Antonini, Giulio +5 more
core +3 more sources
Model order reduction of linear time invariant systems [PDF]
Advances in Radio Science, 2008 This paper addresses issues related to the order reduction of systems with multiple input/output ports. The order reduction is divided up into two steps.
Lj. Radić-Weissenfeld +3 more
doaj
Real-time simulation of the transplanted tooth using model order reduction
Frontiers in Bioengineering and Biotechnology, 2023 The biomechanics of transplanted teeth remain poorly understood due to a lack of models. In this context, finite element (FE) analysis has been used to evaluate the influence of occlusal morphology and root form on the biomechanical behavior of the ...
Pierre Lahoud +20 more
doaj +1 more source
Passivity-preserving parameterized model order reduction using singular values and matrix interpolation [PDF]
, 2013 We present a parameterized model order reduction method based on singular values and matrix interpolation. First, a fast technique using grammians is utilized to estimate the reduced order, and then common projection matrices are used to build ...
Dhaene, Tom +3 more
core +1 more source
ORDER REDUCTION OF DAE MODELS [PDF]
IFAC Proceedings Volumes, 2005 Abstract This report outlines a technique for the order reduction of differential algebraic equations (DAEs). The order reduction is accomplished in two steps. First, algebraic states are partitioned into successive implicit sets of variables and equations by reconstructing the sparsity pattern into lower triangular block form.
John D. Hedengren, Thomas F. Edgar
openaire +1 more source
Stability-preserving model order reduction for linear stochastic Galerkin systems
Journal of Mathematics in Industry, 2019 Mathematical modeling often yields linear dynamical systems in science and engineering. We change physical parameters of the system into random variables to perform an uncertainty quantification.
Roland Pulch
doaj +1 more source
Towards Time-Limited $\mathcal H_2$-Optimal Model Order Reduction [PDF]
, 2017 In order to solve partial differential equations numerically and accurately, a high order spatial discretization is usually needed. Model order reduction (MOR) techniques are often used to reduce the order of spatially-discretized systems and hence ...
Goyal, Pawan, Redmann, Martin
core +3 more sources
Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM
FEBS Letters, EarlyView.Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley +1 more source
, 2021 This is the first chapter of a three-volume series dedicated to theory and application of Model Order Reduction (MOR). We motivate and introduce the basic concepts and notation, with reference to the two main cultural approaches to MOR: the system-theoretic approach employing state-space models and transfer function concepts (Volume 1), and the ...
Benner, P. ; https://orcid.org/0000-0003-3362-4103 +5 more
openaire +2 more sources
Simulation Of Reduction Order Model Ltnear Parameter Varying (Lpv) Systems Using Matlab Software [PDF]
, 2005 The use of optimal control techniques on high-order systems producehigh-order controller. Therefore, an approximation from high-ordersystem to low-order system is needed. The approximation is known asreduction model.
Zuhra, R. (Rahma)
core