重叠三维荧光光谱的解析是荧光光谱解析中的难点, 非负矩阵分解(NMF)作为一种有效的盲分离方法, 能够提取光谱的局部特征和内在联系, 克服光谱严重重叠带来的干扰, 在解析重叠光谱中具有不可比拟的优势。 首先用模拟三维荧光光谱验证了NMF在三维荧光光谱解析中的有效性, 然后将四种不同的NMF算法(乘性迭代算法、 交替最小二乘算法、 二阶方法、 投影梯度算法)用于实测的酚类化合物(百里酚、 间甲酚、 苯酚)三维荧光光谱的解析中, 并讨论了在酚类化合物分离应用中四种NMF算法的收敛速度和计算复杂度的差异。 实验结果表明, 四种方式的NMF标准偏差均在006%以下, 其中交替最小二乘算法在收敛行为和鲁棒性上最为优越。

The present paper primarily tests and verifies the effect of NMF in blind source separation of three-dimensional simulative fluorescence spectra, and then four different computational algorithms (multiplicative iterative; alternating least square; second order method; projected gradient algorithm) were used in three practical phenolic compounds(cresol, phenol, thymol) overlapping fluorescence spectra to find out which nonnegatively constrained algorithms is the most efficient for fluorescence spectra unmixing. The experiments demonstrate that four ways have the normalized residuals below 006%, and alternating least square(ALS) is the best at both convergence behavior and robustness.