3 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Meshless data-driven decompositions with RBF-based inner products
Manuel Ratz, Alessandro Parente, Miguel Alfonso Mendez
Data-driven modal decompositions are useful tools for compressing data or identifying dominant structures. Popular ones like the dynamic mode decomposition (DMD) and the proper ort…
A meshless data-tailored approach to compute statistics from scattered data with adaptive radial basis functions
Damien Rigutto, Manuel Ratz, Miguel A. Mendez
Constrained radial basis function (RBF) regression has recently emerged as a powerful meshless tool for reconstructing continuous velocity fields from scattered flow measurements,…
Meshless Super-Resolution of Scattered Data via constrained RBFs and KNN-Driven Densification
Iacopo Tirelli, Miguel Alfonso Mendez, Andrea Ianiro +1
We propose a novel meshless method to achieve super resolution from scattered data obtained from sparse, randomly positioned sensors such as the particle tracers of particle tracki…
Statistical Methods and Modal Decompositions for Gridded and Scattered Data: Meshless Statistics and Meshless Data Driven Modal Analysis
Miguel A. Mendez, Manuel Ratz, Damien Rigutto
Statistical tools are crucial for studying and modeling turbulent flows, where chaotic velocity fluctuations span a wide range of spatial and temporal scales. Advances in image vel…