论文标题
在实时流媒体上下文中评估原子配对函数（PDF）数据的非负矩阵分解的验证
Validation of non-negative matrix factorization for assessment of atomic pair-distribution function (PDF) data in a real-time streaming context
论文作者
论文摘要
我们验证使用矩阵分解以自动识别来自原子对分布函数（PDF）数据的相关组件。我们还提出了一个新开发的软件基础架构，用于分析以流方式到达的PDF数据。然后，我们应用两种矩阵分解技术，即主成分分析（PCA）和非负矩阵分解（NMF），以在原位实验的背景下研究模拟和实验数据集。
We validate the use of matrix factorization for the automatic identification of relevant components from atomic pair distribution function (PDF) data. We also present a newly developed software infrastructure for analyzing the PDF data arriving in streaming manner. We then apply two matrix factorization techniques, Principal Component Analysis (PCA) and Non-negative Matrix Factorization (NMF), to study simulated and experiment datasets in the context of in situ experiment.
