@article{FackeldeyRoehmNiknejadetal.2021, author = {Fackeldey, Konstantin and R{\"o}hm, Jonas and Niknejad, Amir and Chewle, Surahit and Weber, Marcus}, title = {Analyzing Raman Spectral Data without Separabiliy Assumption}, volume = {3}, journal = {Journal of Mathematical Chemistry}, number = {59}, publisher = {Springer}, arxiv = {http://arxiv.org/abs/2007.06428}, doi = {10.1007/s10910-020-01201-7}, pages = {575 -- 596}, year = {2021}, abstract = {Raman spectroscopy is a well established tool for the analysis of vibration spectra, which then allow for the determination of individual substances in a chemical sample, or for their phase transitions. In the Time-Resolved-Raman-Sprectroscopy the vibration spectra of a chemical sample are recorded sequentially over a time interval, such that conclusions for intermediate products (transients) can be drawn within a chemical process. The observed data-matrix M from a Raman spectroscopy can be regarded as a matrix product of two unknown matrices W and H, where the first is representing the contribution of the spectra and the latter represents the chemical spectra. One approach for obtaining W and H is the non-negative matrix factorization. We propose a novel approach, which does not need the commonly used separability assumption. The performance of this approach is shown on a real world chemical example.}, language = {en} }