| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1234092 | Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy | 2013 | 6 Pages |
An approach for automatic identification of terahertz (THz) spectra of biomolecules is proposed based on principal component analysis (PCA) and fuzzy pattern recognition in this paper, and THz transmittance spectra of some typical amino acid and saccharide biomolecular samples are investigated to prove its feasibility. Firstly, PCA is applied to reduce the dimensionality of the original spectrum data and extract features of the data. Secondly, instead of the original spectrum variables, the selected principal component scores matrix is fed into the model of fuzzy pattern recognition, where a principle of fuzzy closeness based optimization is employed to identify those samples. Results demonstrate that THz spectroscopy combined with PCA and fuzzy pattern recognition can be efficiently utilized for automatic identification of biomolecules. The proposed approach provides a new effective method in the detection and identification of biomolecules using THz spectroscopy.
Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► A deep investigation into the THz spectra of some typical biomolecules. ► PCA is applied to reduce the dimensionality of THz spectrum data and extract features. ► Fuzzy pattern recognition is employed to identify THz spectra of biomolecules. ► This method offers a new effective approach for automatic identification of biomolecules.
