Optimization of multivariable function
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Hi everybody!
I'm having some trouble trying to optimize a function. I want to minimize the function F defined as:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/285331/image.png)
where Aexp is a vector containing experimental data and Asim is a vector of simulated data. The true problem comes when defining the simulation function:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/285332/image.png)
So the optimization needs to be carried out changing a1, sigma and a2 values in order to make F minimum.
However I'm really stuck as I have been using symbolic functions but turns out the result is always 1. I don't know any other way to use integral fucntions, even if this one does not look like working.
Any ideas? Thanks!
5 commentaires
Walter Roberson
le 20 Avr 2020
With that sigma, a1, a2, then the results of Asim are not exactly 0, but they are smaller than 10^(-7000) so double() converts them to 0.
You can, by the way, rewrite:
sigma=5;
a1=1000000;
a2=126;
iarray=linspace(150,400,30);
i1=iarray(1);
syms x y I2
fun1(x,y)=exp(-x/y);
Int1 = int(fun1, y, [i1, I2]);
fun2 = exp((-a1/5)*Int1-(((x-a2)^2)/(2*sigma^2)));
Int2 = int(fun2, x, [0 inf]);
coef=1/(sigma*(2*pi())^0.5);
AAsim = coef*Int2;
aasim = subs(AAsim, I2, iarray);
asim = double(aasim); %fails, values too small for MuPAD to work with
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