Modal decomposition techniques are showing a fast growth in popularity for their wide range
of applications and their various properties, especially as data-driven tools. There are many …

This article presents an innovative open-source software named ModelFLOWs-app, 1
written in Python, which has been created and tested to generate precise and robust hybrid …

Abstract A novel Dynamic Mode Decomposition (DMD) technique capable of handling non–
uniformly sampled data is proposed. As it is usual in DMD analysis, a linear relationship …

This study presents a novel application of data-driven resolvent analysis algorithm for flow
control. The objective is to identify key coherent structures connected to regions of the flow …

In this work, a data-driven, modal decomposition method, the higher order dynamic mode
decomposition (HODMD), is combined with a convolutional neural network (CNN) in order to …

Modern power systems heavily rely on fast and reliable protection and control systems.
However, Sample Value (SV) packets transmitted via Process Bus protocols are susceptible …

This paper introduces a new series of methods which combine modal decomposition
algorithms, such as singular value decomposition and high-order singular value …

The study of images with spatial properties has been a trend in mitigating and
comprehending information from the large and dense image data sets. The grabbed images …