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Studying the Topology and Dynamics of Elasto-inertial Channel Flow Turbulence Using the Invariants of the Velocity Gradient Tensor and Dynamic Mode Decomposition

, 2012
Julio Soria, Vincent Terrapon, Yves Dubief   +2 more
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Analysis on unsteady flow dynamics in a slurry pump based on refinement dynamic mode decomposition

Chen Shao, Minggao Tan, Xianfang Wu, Houlin Liu, Runan Hua, Haochen Ma, Kim Tiow Ooi   +6 more
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Dynamic mode decomposition with memory

Physical Review E, 2023
This study proposed a numerical method of dynamic mode decomposition with memory (DMDm) to analyze multidimensional time-series data with memory effects. The memory effect is a widely observed phenomenon in physics and engineering and is considered to be the result of interactions between the system and environment.
Ryoji, Anzaki, Kei, Sano, Takuro, Tsutsui, Masato, Kazui, Takahito, Matsuzawa   +4 more
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Wavelet‐based dynamic mode decomposition

PAMM, 2021
AbstractDynamic mode decomposition (DMD) has emerged as a leading data‐driven technique to identify the spatio‐temporal coherent structure in dynamical systems, owing to its strong relation with the Koopman operator. For dynamical systems with external forcing, the identified model should not only be suitable for a specific forcing function but should ...
Manu Krishnan, Serkan Gugercin, Pablo Tarazaga   +2 more
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Symbolic extended dynamic mode decomposition

Chaos: An Interdisciplinary Journal of Nonlinear Science
In this paper, we present a new method of performing extended dynamic mode decomposition (EDMD) on systems, which admit a symbolic representation. EDMD generates estimates of the Koopman operator, K, for a dynamical system by defining a dictionary of observables on the space and producing an estimate, Km, which is restricted to be invariant on the span
Connor Kennedy, John Kaushagen, Hong-Kun Zhang   +2 more
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Analysis of Dynamic Stall using Dynamic Mode Decomposition Technique

31st AIAA Applied Aerodynamics Conference, 2013
Dynamic mode decomposition is applied to investigate the unsteady flowfield around a pitching airfoil. The extracted flow structures are termed as dynamic mode decomposition modes. Analyses are performed for both attached flow and dynamic stall cases. Initially, flowfield data generated from numerical simulations are investigated.
Mariappan, Sathesh, Gardner, Anthony Donald, Richter, Kai, Raffel, Markus   +3 more
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Sparse nonnegative dynamic mode decomposition

2017 IEEE International Conference on Image Processing (ICIP), 2017
Dynamic mode decomposition (DMD) is a method to extract coherent modes from nonlinear dynamical systems. In this paper, we propose an extension of DMD, sparse nonnegative DMD, which generates a nonlinear and sparse modal representation of dynamics. In particular, this makes DMD more suitable for video processing.
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi   +2 more
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A Characteristic Dynamic Mode Decomposition

2016
Temporal or spatial structures are readily extracted from complex data by modal decompositions like Proper Orthogonal Decomposition (POD) or Dynamic Mode Decomposition (DMD). Subspaces of such decompositions serve as reduced order models and define either spatial structures in time or temporal structures in space.
Sesterhenn, J��rn, Shahirpour, Amir
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Convergent Dynamic Mode Decomposition

2023 62nd IEEE Conference on Decision and Control (CDC), 2023
Joel A. Rosenfeld, Rushikesh Kamalapurkar   +1 more
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Modern developments in germline pharmacogenomics for oncology prescribing

Ca-A Cancer Journal for Clinicians, 2022
Natalie M Reizine, Peter H O'donnell
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