HELP)) Signal deconvolution using JMP

[#1]

Hello, I'm writing because I have a problem to solve.
The company I work for wants to deconvolution the following Original

The Y-axis is the measured Original value.
The X-axis is a kind of energy intensity expressed in measuring equipment.

What I want to do is to separate(deconvolution) the waveform by finding the peak value according to the X value of the Original Signal expressed for the given Y values.

for example, Black line is Original signal, 

red line is created signal which has peak at 531ev

blue line is created signal which has peak at 532ev...

I would appreciate your help as we are unable to find a suitable Add-In or method for Discussion.

if you could create an Add-In so that we can do this repeatedly.

[#2]

Hi @Dongjin,

it seems that you might need to perform FFT analysis.  These types of functions can be found in the transcendental functions.

see the following Frequency Analysis and Discovery Summit presentation

to get started.  

Others might have more specific examples and use cases on how to proceed.

cheers,

Stan

[#3]

Thank you for your help.
I've reviewed the data you attached, but in fact, what I'm looking for is not a continuous signal, but just a single peak value based on the x-values we want, so I don't think we can apply it immediately.
I should think more about whether there is any other alternative.

[#4 · Accepted solution]

Since this post was written back in 2020, JMP has made numerous improvements in the direction of solving the Peaks Deconvolution problem that was inquired about here.   

In JMP 17 Pro, JMP is much better suited for analyzing peak type data. Basically, there is an alternative way of showing how Wavelet functional data explorer (FDE) and DOE can be used to optimize separation of overlapping peaks for a chromatographic run. For more information, and for anyone currently interested in solving this type with JMP, I recommend the following Developer Tutorial: Modeling Spectral Data Using JMP Pro 17 (available free/ on-demand).

In JMP 18 Pro, there should be more to come in making solving this problem type much easier (more automated). This may include various multivariate curve resolution techniques that will kind of serve as an automated peak identification algorithm. The idea is basically to extract peak widths and to be able to modify those directly.