Results 21 to 30 of about 6,808,722 (274)
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control [PDF]
2020 American Control Conference (ACC), 2020 This paper presents a novel learning framework to construct Koopman eigenfunctions for unknown, nonlinear dynamics using data gathered from experiments. The learning framework can extract spectral information from the full nonlinear dynamics by learning the eigenvalues and eigenfunctions of the associated Koopman operator.
Folkestad, Carl +5 more
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Extended dynamic mode decomposition for cyclic macroeconomic data
Data Science in Finance and Economics, 2022 <abstract><p>We apply methods from the Koopman operator theory, Extended Dynamic Mode Decomposition and machine learning in the study of business cycle models. We use a simple non-linear dynamical system whose main merit is that in the appropriate parameter space sector predicts intrinsically business cycles which in the phase space are ...
John Leventides +2 more
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A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition [PDF]
Journal of Nonlinear Science, 2015 The Koopman operator is a linear but infinite dimensional operator that governs the evolution of scalar observables defined on the state space of an autonomous dynamical system, and is a powerful tool for the analysis and decomposition of nonlinear dynamical systems.
Matthew O. Williams +2 more
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Scale-Separated Dynamic Mode Decomposition
, 2022 MatLab code to implement the Scale-Separated Dynamic Mode Decomposition method on electron density profile data ...
Alford-Lago
core +1 more source
Measurement + Control, 2022 Omnidirectional mobile manipulators (OMMs) have been widely used due to their high mobility and operating flexibility. However, since OMMs are complex nonlinear systems with uncertainties, the dynamic modeling and control are always challenging problems.
Xuehong Zhu +3 more
doaj +1 more source
A quantitative analysis of Koopman operator methods for system identification and predictions
Comptes Rendus. Mécanique, 2022 We give convergence and cost estimates for a data-driven system identification method: given an unknown dynamical system, the aim is to recover its vector field and its flow from trajectory data.
Zhang, Christophe, Zuazua, Enrique
doaj +1 more source
Engineering Science and Technology, an International Journal, 2018 The aim of this paper is to reveal the effectiveness of Adomian decomposition method (ADM) and differential transform method (DTM) on free vibrations of axial-loaded Timoshenko beams resting on viscoelastic foundation.
Baran Bozyigit +2 more
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Journal of Low Frequency Noise, Vibration and Active Control, 2018 Civil engineering structures in essence belong to time-varying and nonlinear structures and the resultant dynamic responses are usually nonstationary signals. A new method is proposed to extract instantaneous frequency of such nonstationary signals.
Jing-Liang Liu +4 more
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Infrastructures, 2022 Even though prefabricated steel Bailey bridges have been used for more than 80 years, limited studies of their structural features have been conducted, most of which do not consider their response in operational conditions.
Vasileios D. Papavasileiou +3 more
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Extended Nodal Admittance Matrix Based Stability Analysis of HVDC Connected AC Grids
IEEE Access, 2022 Motivated by emerging HVDC oscillation issues resulted from the interaction with AC grids, impedance-based stability analysis has become an attractive approach in the de-risking studies due to the capability of black-box modelling and clear physical ...
Yonggang Zhang +3 more
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