Non-negative matrix factorization (NMF) has been frequently used in research on live cells, biomolecules, and tissues (bio-Raman research) to disentangle the complicated and large sized data. A stagnation is that NMF does not provide unique decomposition, depending on initial settings; that is, NMF returns non-negative spectral components close to the truths, but solely giving several possibilities. In this research, we visualized possible ranges of NMF in binary component system. The mechanism of NMF became more clarified and opened new viewpoints.

中文翻译：

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期待生物拉曼研究的非负因式分解的图形解释

非负矩阵分解 (NMF) 经常用于活细胞、生物分子和组织的研究（生物拉曼研究），以解开复杂和大尺寸的数据。一个停滞是 NMF 不提供唯一的分解，这取决于初始设置；也就是说，NMF 返回接近事实的非负谱分量，但仅给出了几种可能性。在这项研究中，我们可视化了二元组分系统中 NMF 的可能范围。NMF的机制更加清晰，并开辟了新的观点。