Conference paper
A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Cognitive Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Department of Micro- and Nanotechnology, Technical University of Denmark3
Nanoprobes, Department of Micro- and Nanotechnology, Technical University of Denmark4
Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Department of Health Technology, Technical University of Denmark5
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: | 2317-21 |
Proceedings: | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing |
ISBN: | 1509041168 and 9781509041169 |
Types: | Conference paper |
DOI: | 10.1109/ICASSP.2017.7952570 |
ORCIDs: | Alstrøm, Tommy Sonne , Schmidt, Mikkel Nørgaard , Rindzevicius, Tomas , Boisen, Anja and Larsen, Jan |