how to use lsqnonlin to solve conditional equation
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cheng li
am 5 Sep. 2021
Kommentiert: cheng li
am 8 Sep. 2021
i would like to input the following equation in matlab and use lsqnonlin to find the C0, Cinfi1, k1, t2start, Cinfi2 and k2 that can fit an obriginal data?
Are there anyone knowning how to do that?
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Fabio Freschi
am 7 Sep. 2021
Bearbeitet: Fabio Freschi
am 7 Sep. 2021
The following code should be self explainatory. In the opposite case, simply ask
clear all, close all
% some dummy params values
C0 = 2;
Cinf1 = 10;
k1 = 2;
t2start = 3;
Cinf2 = 8;
k2 = 3;
% t vector
tData = linspace(0,10,50);
% data + noise
rng(0); % for reproducibility
yData = C0+Cinf1*(1-exp(-k1*tData))+(tData >= t2start).*(Cinf2*(1-exp(-k2*(tData-t2start))))+0.3*randn(size(tData));
% anonymous function for fitting (function-data) that must be minimized
% using least squares
% x(1) = C0
% x(2) = Cinf1
% x(3) = k1
% x(4) = t2start
% x(5) = Cinf2
% x(6) = k2
C = @(x)x(1)+x(2)*(1-exp(-x(3)*tData))+(tData >= x(4)).*(x(5)*(1-exp(-x(6)*(tData-x(4)))))-yData;
% initial values (experience may help here)
x0 = [1 1 1 1 1 1];
% fitting
x = lsqnonlin(C,x0);
% plot
figure, hold on
plot(tData,yData,'o');
% reconstruction of the best fit from the anonymous function
plot(tData,C(x)+yData);
legend('data','best fit');
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