Abstract
Raman spectroscopy is a well-known analytical technique for identifying and analyzing chemical species. Since Raman scattering is a weak effect, surface-enhanced Raman spectroscopy (SERS) is often employed to amplify the signal. SERS signal surface mapping is a common method for detecting trace amounts of target molecules. Since the method produce large amounts of data and, in the case of very low concentrations, low signal-to-noise (SNR) ratio, ability to extract relevant spectral features is crucial. We propose a pseudo-Voigt model as a constrained source separation model, that is able to directly and reliably identify the Raman modes, with overall performance similar to the state of the art non-negative matrix factorization approach. However, the model provides better interpretation and is a step towards enabling the use of SERS in detection of trace amounts of molecules in real-life settings.
Original language | English |
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Title of host publication | Proceedings of the 42nd IEEE International Conference on Acostics, Speech and Signal Processing |
Publisher | IEEE |
Publication date | 2017 |
Pages | 2317-21 |
ISBN (Print) | 9781509041169 |
DOIs | |
Publication status | Published - 2017 |
Event | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing - Hilton New Orleans Riverside, New Orleans, United States Duration: 5 Mar 2017 → 9 Mar 2017 Conference number: 42 http://www.ieee-icassp2017.org/ |
Conference
Conference | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing |
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Number | 42 |
Location | Hilton New Orleans Riverside |
Country/Territory | United States |
City | New Orleans |
Period | 05/03/2017 → 09/03/2017 |
Internet address |