Signal conditioning in Raman Spectroscopy Signals
Is there a way to tackel the baseline problem in Raman Spectroscopy ?
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Within this book the use of MatLab as a means to analyze Raman spectroscopy data is explored. Raman measurements of a wide range of biological building blocks, with an increasing degree of complexity, were taken and whole cells were analyzed. The associated peaks were assigned and possible noise sources and sources of baseline were discussed and the generated signals were exported from Labspec into Mathworks MatLab, then analyzed by differentiation and filtering. With a combination of classical approaches and specially designed ones the baseline of signals were automatically identified and con...
Within this book the use of MatLab as a means to analyze Raman spectroscopy data is explored. Raman measurements of a wide range of biological building blocks, with an increasing degree of complexity, were taken and whole cells were analyzed. The associated peaks were assigned and possible noise sources and sources of baseline were discussed and the generated signals were exported from Labspec into Mathworks MatLab, then analyzed by differentiation and filtering. With a combination of classical approaches and specially designed ones the baseline of signals were automatically identified and consequently subtracted. This procedure was applied to artificial signals as well as to the real taken spectra and then compared regarding their significance, paving the way to a fully automated baseline subtraction regime.
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