2010
DOI: 10.2478/v10178-010-0045-1
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Algorithms of Chemicals Detection Using Raman Spectra

Abstract: Raman spectrometers are devices which enable fast and non-contact identification of examined chemicals. These devices utilize the Raman phenomenon to identify unknown and often illicit chemicals (e.g. drugs, explosives) without the necessity of their preparation. Now, Raman devices can be portable and therefore can be more widely used to improve security at public places. Unfortunately, Raman spectra measurements is a challenge due to noise and interferences present outside the laboratories. The design of a po… Show more

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Cited by 45 publications
(33 citation statements)
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“…We should underscore that the method does not require any additional data processing (e.g., background noise removal, spectra smoothing, etc. ), which is common in other chemo-metric methods [25]. This is a benefit of the LS-SVM method, because any additional pre-processing method demands optimal selection of some additional parameters before its use.…”
Section: Gas Concentration [Ppm]mentioning
confidence: 99%
“…We should underscore that the method does not require any additional data processing (e.g., background noise removal, spectra smoothing, etc. ), which is common in other chemo-metric methods [25]. This is a benefit of the LS-SVM method, because any additional pre-processing method demands optimal selection of some additional parameters before its use.…”
Section: Gas Concentration [Ppm]mentioning
confidence: 99%
“…Since the continuum background is broad and featureless, previous investigators have employed several numerical post-processing schemes to approximate and remove it from the acquired spectral data [17], [18]. Here, the background of the LIBS spectra was removed by application of an iterative least squares-based curve-fitting algorithm that uses a polynomial (6 th order for our dataset) with non-negativity constraints [19].…”
Section: Discussionmentioning
confidence: 99%
“…We conclude, that a quantitative analysis may be carried out with grater dataset, which will allow statistical approach by employing multivariate models and classification algorithms [18][19][20][21], such as principle component analysis (PCA), partial least-square (PLS) regression, or support vector machines (SVM). Such approach will enable to determine the quantities of specific compounds in blood.…”
Section: A) B)mentioning
confidence: 99%