Results 31 to 40 of about 3,075 (261)
Wireless Technology Identification Employing Dynamic Mode Decomposition Modeling
IEEE Access, 2023 Significant growth in broadband wireless services, as well as ever-increasing demand on the spectrum caused by the Internet of Things (IoT) have overstretched limited available spectrum space for wireless services.
Ahmed Elsebaay, Hazem H. Refai
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Extended dynamic mode decomposition for cyclic macroeconomic data
Data Science in Finance and Economics, 2022 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 ...
John Leventides +2 more
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Dynamic mode decomposition of the geomagnetic field over the last two decades
Earth and Planetary Physics, 2023 Earth's magnetic field, which is generated in the liquid outer core through the dynamo action, undergoes changes on timescales of a few years to several million years, yet the underlying mechanisms responsible for the field variations remain to be ...
JuYuan Xu, YuFeng Lin
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High dynamic range spatial mode decomposition
Optics Express, 2020 An accurate readout of low-power optical higher-order spatial modes is of increasing importance to the precision metrology community. Mode sensors are used to prevent mode mismatches from degrading quantum and thermal noise mitigation strategies. Direct mode analysis sensors (MODAN) are a promising technology for real-time monitoring of arbitrary ...
A. W. Jones +3 more
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Machine learning enhanced Hankel dynamic-mode decomposition
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 While the acquisition of time series has become more straightforward, developing dynamical models from time series is still a challenging and evolving problem domain. Within the last several years, to address this problem, there has been a merging of machine learning tools with what is called the dynamic-mode decomposition (DMD).
Christopher W. Curtis +3 more
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Data-Driven modeling for Li-ion battery using dynamic mode decomposition
Alexandria Engineering Journal, 2022 Lithium-ion (Li-ion) batteries are the workhorse of energy storage systems in electric vehicles (EVs) due to their high energy density and desirable characteristics.
Mohamed A. Abu-Seif +4 more
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Prediction Accuracy of Dynamic Mode Decomposition
SIAM Journal on Scientific Computing, 2020 Dynamic mode decomposition (DMD), which the family of singular-value decompositions (SVD), is a popular tool of data-driven regression. While multiple numerical tests demonstrated the power and efficiency of DMD in representing data (i.e., in the interpolation mode), applications of DMD as a predictive tool (i.e., in the extrapolation mode) are scarce.
Hannah Lu, Daniel M. Tartakovsky
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Bayesian Dynamic Mode Decomposition [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Dynamic mode decomposition (DMD) is a data-driven method for calculating a modal representation of a nonlinear dynamical system, and it has been utilized in various fields of science and engineering. In this paper, we propose Bayesian DMD, which provides a principled way to transfer the advantages of the Bayesian formulation into DMD.
Naoya Takeishi +3 more
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Optimal low-rank Dynamic Mode Decomposition [PDF]
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASPP), New Orleans, USA ...
Héas, Patrick, Herzet, Cédric
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Dynamic Mode Decomposition with Control Liouville Operators
IFAC-PapersOnLine, 2021 This paper builds the theoretical foundations for dynamic mode decomposition (DMD) of control-affine dynamical systems by leveraging the theory of vector-valued reproducing kernel Hilbert spaces (RKHSs). Specifically, control Liouville operators and control occupation kernels are introduced to separate the drift dynamics from the input dynamics.
Joel A. Rosenfeld +1 more
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