Optimal Kernel-Based Dynamic Mode Decomposition
, 2017 The state-of-the-art algorithm known as kernel-based dynamic mode decomposition (K-DMD) provides a sub-optimal solution to the problem of reduced modeling of a dynamical system based on a finite approximation of the Koopman operator.
Héas, Patrick, Herzet, Cédric
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Efficient and robust background modeling with dynamic mode decomposition
A large number of modern video background modeling algorithms deal with computational costly minimization problems that often need parameter adjustments.
Weiskopf, Daniel +3 more
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RRAEDy: adaptive latent linearization of nonlinear dynamical systems. [PDF]
Sci RepMounayer J +4 more
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Kernel-DMD for multiome data integration and control. [PDF]
PLoS Comput BiolPierides I +3 more
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On Chinese space station: pioneering space experiments unraveling the hydrodynamic instability of annular thermocapillary convection. [PDF]
Sci RepWu D +5 more
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Dynamic Mode Decomposition with Non-uniform Sampling
Dynamic Mode Decomposition (DMD) and its extensions (EDMD) have been at the forefront of data-based approaches to Koopman operators. Most (E)DMD algorithms assume that the entire state is sampled at a uniform sampling rate.
Anantharaman, Ramachandran +1 more
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An Anti-Interference Demultiplexing Method for Electromagnetic Bessel Beams Carrying Orbital Angular Momentum. [PDF]
Sensors (Basel)Mi C, Huang X, Qiao W, Zhang Y.
europepmc +1 more source
Unveiling individual and collective temporal patterns in the tanker shipping network. [PDF]
Nat CommunTeo K +6 more
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We introduce the Rigged Dynamic Mode Decomposition (Rigged DMD) algorithm, which computes generalized eigenfunction decompositions of Koopman operators.
Drysdale, Catherine +2 more
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CNN-based framework for Alzheimer's disease detection from EEG via dynamic mode decomposition. [PDF]
Front NeuroinformKang J, Kang H, Seo JH.
europepmc +1 more source