Opt Lett. 2019 Dec 1;44(23):5836-5839. doi: 10.1364/OL.44.005836.
Classification of different species with Raman measurements is analyzed when a total of exactly $ N $N photons are detected with binary filtered Raman spectra instead of fixing the measuring time. The optimal classification method for this problem leads to classification error probabilities upper-bounded by the Bhattacharyya bound and that are invariant to the multiplication of the spectrum intensities by an unknown factor. Furthermore, it is shown that this approach can be implemented with a number of binary filters smaller than the number of species to discriminate.
当使用二进制滤波拉曼光谱总共检测到恰好 $ N $ 个光子，而不是固定测量时间时，分析了使用拉曼测量对不同物种进行分类的情况。对于这个问题，最优的分类方法导致分类错误概率被 Bhattacharyya 界所上界限制，并且与光谱强度乘以未知因子的乘积无关。此外，还表明，这种方法可以用比要区分的物种数量少的二进制滤波器数量来实现。
