A novel coupling of noise reduction algorithms for particle flow simulations

DOI10.1016/j.jcp.2016.05.049zbMath1349.74381OpenAlexW2394489076WikidataQ59765925 ScholiaQ59765925MaRDI QIDQ726922

M. J. Zimoń, Jason M. Reese, David R. Emerson

Publication date: 5 December 2016

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2016.05.049

zbMATH Keywords

molecular dynamicsdissipative particle dynamicswavelet thresholdingnoise reductionparticle-based simulationswindowed proper orthogonal decomposition

Mathematics Subject Classification ID

Related Items (2)

Generalized Lagrangian heterogeneous multiscale modelling of complex fluids ⋮ Time-resolved denoising using model order reduction, dynamic mode decomposition, and Kalman filter and smoother

Cites Work

• Multivariate denoising using wavelets and principal component analysis
• Transport properties of liquid argon in krypton nanochannels: Anisotropy and non-homogeneity introduced by the solid walls
• Microflows and nanoflows. Fundamentals and simulation. Foreword by Chih-Ming Ho.
• The Optimal Hard Threshold for Singular Values is <inline-formula> <tex-math notation="TeX">\(4/\sqrt {3}\) </tex-math></inline-formula>
• A theory for multiresolution signal decomposition: the wavelet representation
• Fast computation of low-rank matrix approximations
• Ten Lectures on Wavelets
• Turbulence, Coherent Structures, Dynamical Systems and Symmetry
• Ideal spatial adaptation by wavelet shrinkage
• Analysing and Computing Turbulent Flows Using Wavelets
• De-noising by soft-thresholding
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: A novel coupling of noise reduction algorithms for particle flow simulations