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For example, I have the next spectrum:

I've seen the next question ["How to perform a multi-peak fitting?"][2]

but not answer to my question. I want deconvolution the spectrum to obtain three peaks (how Origin to do it). The sum of these three peaks gives the total spectrum. I know fit each peaks with gaussian or lorentziana function (or mixture of both) but this is different to deconvolution. My interest for deconvolution is find the FWHM each peak.

Are there codes for deconvolution data similar to mine?.

These are the datas of the spectrum: [Spectrum data][3]

[2]: How to perform a multi-peak fitting? multi-peak-fitting [3]: https://www.cubbyusercontent.com/pli/Spectrum.txt/_518b3bdb5f87485d885dda9875448397

This the code with the function for fitting each peak:

modelL = (2*A/Pi)*(w/(4*(x - xc)^2 + w^2));
modelGfh = A/(w*Sqrt[Pi/4 Log[2]])*E^(-4*Log[2]*(x - xc)^2/w^2);
r = 0.2;
modelLGfh = r*modelL + (1 - r)*modelGfh;
nlmD = NonlinearModelFit[peak1, 
modelLGfh, {{A, 1}, {w, 1}, {xc, 441}}, x, MaxIterations -> 10000];

For example, I have the next spectrum:

I've seen the next question ["How to perform a multi-peak fitting?"][2]

but not answer to my question. I want deconvolution the spectrum to obtain three peaks (how Origin to do it). The sum of these three peaks gives the total spectrum. I know fit each peaks with gaussian or lorentziana function (or mixture of both) but this is different to deconvolution. My interest for deconvolution is find the FWHM each peak.

Are there codes for deconvolution data similar to mine?.

These are the datas of the spectrum: [Spectrum data][3]

[2]: How to perform a multi-peak fitting? multi-peak-fitting [3]: https://www.cubbyusercontent.com/pli/Spectrum.txt/_518b3bdb5f87485d885dda9875448397

This the code with the function for fitting each peak:

modelL = (2*A/Pi)*(w/(4*(x - xc)^2 + w^2));
modelGfh = A/(w*Sqrt[Pi/4 Log[2]])*E^(-4*Log[2]*(x - xc)^2/w^2);
r = 0.2;
modelLGfh = r*modelL + (1 - r)*modelGfh;
nlmD = NonlinearModelFit[peak1, 
modelLGfh, {{A, 1}, {w, 1}, {xc, 441}}, x, MaxIterations -> 10000];

For example, I have the next spectrum:

I've seen the next question ["How to perform a multi-peak fitting?"][2]

but not answer to my question. I want deconvolution the spectrum to obtain three peaks (how Origin to do it). The sum of these three peaks gives the total spectrum. I know fit each peaks with gaussian or lorentziana function (or mixture of both) but this is different to deconvolution. My interest for deconvolution is find the FWHM each peak.

Are there codes for deconvolution data similar to mine?.

These are the datas of the spectrum: [Spectrum data][3]

[2]: How to perform a multi-peak fitting? multi-peak-fitting [3]: https://www.cubbyusercontent.com/pli/Spectrum.txt/_518b3bdb5f87485d885dda9875448397

This the code with the function for fitting each peak:

modelL = (2*A/Pi)*(w/(4*(x - xc)^2 + w^2));
modelG = A/(w*Sqrt[Pi/2])*E^(-2 (x - xc)^2/w^2);
modelGfh = A/(w*Sqrt[Pi/4 Log[2]])*E^(-4*Log[2]*(x - xc)^2/w^2);
r = 0.2;
modelLGfh = r*modelL + (1 - r)*modelGfh;
nlmD = NonlinearModelFit[peak1, 
modelLGfh, {{A, 1}, {w, 1}, {xc, 441}}, x, MaxIterations -> 10000];

For example, I have the next spectrum:

I've seen the next question ["How to perform a multi-peak fitting?"][2]

but not answer to my question. I want deconvolution the spectrum to obtain three peaks (how Origin to do it). The sum of these three peaks gives the total spectrum. I know fit each peaks with gaussian or lorentziana function (or mixture of both) but this is different to deconvolution. My interest for deconvolution is find the FWHM each peak.

Are there codes for deconvolution data similar to mine?.

These are the datas of the spectrum: [Spectrum data][3]

[2]: How to perform a multi-peak fitting? multi-peak-fitting [3]: https://www.cubbyusercontent.com/pli/Spectrum.txt/_518b3bdb5f87485d885dda9875448397

This the code with the function for fitting each peak:

modelL = (2*A/Pi)*(w/(4*(x - xc)^2 + w^2));
modelGfh = A/(w*Sqrt[Pi/4 Log[2]])*E^(-4*Log[2]*(x - xc)^2/w^2);
r = 0.2;
modelLGfh = r*modelL + (1 - r)*modelGfh;
nlmD = NonlinearModelFit[peak1, 
modelLGfh, {{A, 1}, {w, 1}, {xc, 441}}, x, MaxIterations -> 10000];