Results 61 to 70 of about 287,879 (312)
On the correspondence between Koopman mode decomposition, resolvent mode decomposition, and invariant solutions of the Navier-Stokes equations [PDF]
, 2016 The relationship between Koopman mode decomposition, resolvent mode decomposition and exact invariant solutions of the Navier-Stokes equations is clarified.
McKeon, Beverley J. +2 more
core +3 more sources
Spectral proper orthogonal decomposition [PDF]
, 2015 The identification of coherent structures from experimental or numerical data is an essential task when conducting research in fluid dynamics. This typically involves the construction of an empirical mode base that appropriately captures the dominant ...
Oberleithner, Kilian +2 more
core +2 more sources
Multiplicative Dynamic Mode Decomposition
SIAM Journal on Applied Dynamical Systems24 pages, 13 figures.
Nicolas Boullé, Matthew J. Colbrook
openaire +3 more sources
Automatic Seizure Detection Using Multi-Resolution Dynamic Mode Decomposition
IEEE Access, 2019 Epilepsy is one of the most prevalent neurological issues faced by a large population around the globe. Epilepsy is marked by intermittent seizures, the detection of which can be a challenging problem.
Muhammad Bilal +5 more
doaj +1 more source
Physics-informed dynamic mode decomposition
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023 In this work, we demonstrate how physical principles—such as symmetries, invariances and conservation laws—can be integrated into the dynamic mode decomposition (DMD). DMD is a widely used data analysis technique that extracts low-rank modal structures and dynamics from high-dimensional ...
Peter J. Baddoo +4 more
openaire +2 more sources
Centering Data Improves the Dynamic Mode Decomposition [PDF]
SIAM Journal on Applied Dynamical Systems, 2020 Dynamic mode decomposition (DMD) is a data-driven method that models high-dimensional time series as a sum of spatiotemporal modes, where the temporal modes are constrained by linear dynamics. For nonlinear dynamical systems exhibiting strongly coherent structures, DMD can be a useful approximation to extract dominant, interpretable modes.
Seth M. Hirsh +3 more
openaire +3 more sources
Molecular Oncology, EarlyView.Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice +16 more
wiley +1 more source
Analyzing Nonlinear Dynamics via Data-Driven Dynamic Mode Decomposition-Like Methods
Complexity, 2018 This article presents a review on two methods based on dynamic mode decomposition and its multiple applications, focusing on higher order dynamic mode decomposition (which provides a purely temporal Fourier-like decomposition) and spatiotemporal Koopman ...
Soledad Le Clainche, José M. Vega
doaj +1 more source
Sensors, 2022 In order to study the characteristics of pressure fluctuation during unstable combustion, experimental studies had been conducted on the mechanism model of the swirl combustor and the industrial swirl combustor.
Xuhuai Wang +4 more
doaj +1 more source
Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity
Molecular Oncology, EarlyView.Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung +17 more
wiley +1 more source