Raman spectroscopy: data analysis: convolution

In summary, the speaker is seeking help with their task of analyzing Raman spectroscopy data and deconvoluting it. They are unsure if the raw data they receive is already convoluted or if they need to convolute it themselves. Another person clarifies that the raw data is indeed convoluted due to imperfections in the detector, and explains the process of using the Fourier transform to deconvolute the data. The speaker then confirms that they have successfully used the Gaussian curve to deconvolute their data and thanks the other person for their detailed answer.
  • #1
liss
2
0
hey guys,
i hope you can help.

my task is to analyse data of raman spectroscopy. therefor i have to deconvolute it. that means the data must have been convoluted somewhere.

is it true that the raw data which i receive is convoluted already? or is it common to convolute the data "active"?
i guess its a stupid question but i am not quite sure.

thanks in regard
 
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  • #2
its a very good question if you haven't come across convolution method before. i had the same question a few months ago on my medical imaging course. the idea is that the data you take from any detector, is imperfect and as a result, the raw data you get is a convolution of the Fourier transform of your detector and the data. so information about the Fourier transform of your detector will allow you to do the inverse transformation, and then the raw data is just multiplied by the inverse Fourier transform to give your final data. i am unforunately not very familiar with the raman spectrometer detectors, but I am sure they have basic experiments run on them to determine the information about their detectors
 
  • #3
thank you so much for your detailed answer, i got it now.

as far as i can remember we used the gaussian curve to deconvolute the data based on a hint of my prof. and it worked out.
only when i prepared my talk i have wondered where the convolution takes place.
so your answer suffices absolutly :)
 
  • #4
woopy :P
 

FAQ: Raman spectroscopy: data analysis: convolution

1. What is Raman spectroscopy?

Raman spectroscopy is a technique used to analyze the vibrational and rotational energy levels of molecules. It involves shining a laser onto a sample and measuring the scattered light, which can provide information about the chemical composition and structure of the sample.

2. How does Raman spectroscopy work?

In Raman spectroscopy, a laser is used to irradiate a sample, causing the molecules to vibrate and rotate. Some of the scattered light will have a different energy (wavelength) than the incident laser light, which is known as the Raman effect. This scattered light is then analyzed to determine the molecular properties of the sample.

3. What is data analysis in Raman spectroscopy?

Data analysis in Raman spectroscopy involves processing and interpreting the data collected from the sample. This can include removing background noise, correcting for instrument effects, and identifying specific peaks in the spectrum to determine the chemical composition of the sample.

4. What is convolution in Raman spectroscopy data analysis?

Convolution is a mathematical operation used in Raman spectroscopy data analysis to smooth and enhance the spectrum. It involves multiplying the spectrum by a mathematical function, known as a kernel, to reduce noise and improve the resolution of the peaks.

5. How is convolution used in Raman spectroscopy data analysis?

Convolution is used in Raman spectroscopy data analysis to improve the signal-to-noise ratio and enhance the resolution of the spectrum. It helps to identify smaller peaks that may be hidden by background noise, and can also be used to remove unwanted features from the spectrum, such as fluorescence. Different kernels can be applied depending on the type of analysis being performed on the Raman data.

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