Deconvolution of Guassian curve
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I have a curve here which I have to deconvolve it into many other curves with different peaks. The resault is this in another program:
That is I have to deconvolve one curve in 4 curves in Matlab! I want to do the same thing in Matlab but I failed!
clc
clear all
D398=importdata('J398.txt');
D398=flipud(D398); %its a spectrum from higher values to smaller!
X1=D398(:,1); Y1=D398(:,2);
[X,Y]=deconv(X1,Y1);
plot(X1,Y1)
hold on
plot(X,Y,'r')
set(gca, 'XDir','reverse')
grid on
But it is not correct! Is that possible to do this in Matlab ?
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Answers (1)
Alex Sha
on 5 May 2020
Hi, you may try 4 Gauss Function:
The results will be:
Root of Mean Square Error (RMSE): 451.21462729511
Sum of Squared Residual: 49066308.2123007
Correlation Coef. (R): 0.999771552934335
R-Square: 0.999543158056732
Adjusted R-Square: 0.999539319048805
Determination Coef. (DC): 0.999543158056733
Parameter Best Estimate
---------- -------------
y0 6181.08011049796
a1 -3146.47497260807
w1 1.88004200222529
xc1 528.043585459549
a2 67855.6616645231
w2 1.23677625792812
xc2 533.256290476665
a3 89669.8140293669
w3 1.73388329145185
xc3 531.944238118754
a4 -58214.4714395774
w4 -1.73177439354019
xc4 534.823600475954
5 Comments
Alex Sha
on 25 Feb 2021
Hi, Dang, the result given above is obtained by a software package other than Matlab, with the great ability of global optimization. The curve fitting functions in Matlan use normally local optimization algorithms, so you should usually gauss and provide proper initial start values for each parameters, unfortunately, it is a really hard and difficulty job for most of peoples.
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