Results 91 to 100 of about 31,410,548 (207)
Enhanced Subspace Dynamic Mode Decomposition for Operational Modal Analysis of Aerospace Structures
To address the issue of low accuracy in the dynamic modal decomposition (DMD) method used for operational modal analysis (OMA) under noise conditions of aerospace structures, an enhanced identification approach is proposed in this paper, which integrates
Hao Zheng, Rui Zhu, Yanbin Li
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Abstract Models of Transfinite Reductions.
We investigate transfinite reductions in abstract reduction systems. To this end, we study two abstract models for transfinite reductions: a metric model generalising the usual metric approach to infinitary term rewriting and a novel partial order model.
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A Hybrid Model Reduction Method for Dual-Continuum Model with Random Inputs
In this paper, a hybrid model reduction method for solving flows in fractured media is proposed. The approach integrates the Generalized Multiscale Finite Element Method (GMsFEM) with a novel variable-separation (VS) technique.
Lingling Ma
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This paper proposes a hybrid time–frequency domain identification method for second-order plus dead time models with an additional process zero (SOPDT+Z).
Joon-Ho Cho
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Model Order Reduction in Neuroscience
The human brain contains approximately $10^9$ neurons, each with approximately $10^3$ connections, synapses, with other neurons. Most sensory, cognitive and motor functions of our brains depend on the interaction of a large population of neurons. In recent years, many technologies are developed for recording large numbers of neurons either sequentially
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This paper presents an estimation of transient stability regions for large-scale power systems. In Part I, a Koopman operator based model reduction (KOMR) method is proposed to derive a low-order dynamical model with reasonable accuracy for transient ...
Yuqing Lin +4 more
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PeakForce AFM Analysis Enhanced with Model Reduction Techniques. [PDF]
Chang X, Hallais S, Danas K, Roux S.
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Average current mode controller for bridgeless PFC SEPIC converter with second-order model reduction operated in continuous conduction mode. [PDF]
Rai NA +5 more
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Data-driven nonlinear model reduction to spectral submanifolds in mechanical systems. [PDF]
Cenedese M +4 more
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Hybrid Models and Biological Model Reduction with PyDSTool
The PyDSTool software environment is designed to develop, simulate, and analyze dynamical systems models, particularly for biological applications. Unlike the engineering application focus and graphical specification environments of most general purpose simulation tools, PyDSTool provides a programmatic environment well suited to exploratory data- and ...
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