Conference paper
A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy
Dept. of Appl. Math. & Comput. Sci., Tech. Univ. of Denmark, Lyngby, Denmark1
Dept. of Micro & Nanotechnol., Tech. Univ. of Denmark, Lyngby, Denmark2
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.
Language: | English |
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Publisher: | IEEE |
Year: | 2017 |
Pages: | 2317-2321 |
Proceedings: | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
ISBN: | 1509041168 , 1509041176 , 1509041184 , 9781509041169 , 9781509041176 and 9781509041183 |
ISSN: | 2379190x and 15206149 |
Types: | Conference paper |
DOI: | 10.1109/ICASSP.2017.7952570 |