MODULO：数据多尺度正交分解软件
MODULO: A software for Multiscale Proper Orthogonal Decomposition of data
摘要：
在大数据革命的时代，在大数据集中自动发现数据的方法正在成为应用科学中必不可少的工具。本文介绍了一个开放的软件包，名为MODULO（MODal mULtisale pOd），执行多尺度本征正交分解（mPOD）的数值和实验数据。这种新的分解结合了多分辨率分析（MRA）和标准的本征正交分解（POD），以允许其模式的分解收敛性和频谱纯度之间的最佳折衷。该软件配备了图形用户界面（GUI），并通过大量示例和视频教程进行了丰富（参见Youtube频道MODULO mPOD）。可在\url{https://github.com/mendezVKI/MODULO/releases}下载MATLAB源代码和Windows用户可执行文件; \url{https://github.com/mendezVKI/MODULO}中提供了Matlab和Python练习集
英文摘要：
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}
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
