AI RESEARCH
A Brain-Inspired Deep Separation Network for Single Channel Raman Spectra Unmixing
arXiv CS.LG
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ArXi:2604.22324v1 Announce Type: new Raman spectra obtained in real world applications are often a noisy combination of several spectra of various substances in a tested sample. Unmixing such spectra into individual components corresponding to each of the substances is of great value and has been a longstanding challenge in Raman spectroscopy. Existing unmixing methods are predominantly designed to invert an overdetermined mixed model and therefore require multiple mixed spectra as input.