论文标题
Modulo：用于多尺度正确正交分解数据的软件
MODULO: A software for Multiscale Proper Orthogonal Decomposition of data
论文作者
论文摘要
在大数据革命的时代，在大型数据集中自动发现规律性的方法正在成为应用科学的重要工具。本文介绍了一个名为Modulo（模态多尺度POD）的开放软件包，以执行数值和实验数据的多尺度正交分解（MPOD）。这种新颖的分解结合了多分辨率分析（MRA）和标准的正交分解（POD），以允许其模式的分解收敛和光谱纯度之间的最佳折衷。该软件配备了图形用户界面（GUI），并包含许多示例和视频教程（请参阅YouTube Channel Modulo MPOD）。可以在\ url {https://github.com/mendezvki/modulo/releases}下载MATLAB源代码和Windows用户的可执行文件}; \ url {https://github.com/mendezvki/modulo}提供了Matlab和Python的练习集合。
In the era of the Big Data revolution, methods for the automatic discovery of regularities in large datasets are becoming essential tools in applied sciences. This article presents an open software package, named MODULO (MODal mULtiscale pOd), to perform the Multiscale Proper Orthogonal Decomposition (mPOD) of numerical and experimental data. This novel decomposition combines Multi-resolution Analysis (MRA) and standard Proper Orthogonal Decomposition (POD) to allow for the optimal compromise between decomposition convergence and spectral purity of its modes. The software is equipped with a Graphical User Interface (GUI) and enriched by numerous examples and video tutorials (see Youtube channel MODULO mPOD). The MATLAB source codes and an executable for Windows users can be downloaded at \url{https://github.com/mendezVKI/MODULO/releases}; a collection of exercises in Matlab and Python are provided in \url{https://github.com/mendezVKI/MODULO}
