Problem with optimizing a function which has indirect variables (variables are a set of data that is generated with the help of another function)
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I desperately need to find a way to solve this for my work ,
i have a certain function which calculates the fit of my chosen parameters, i have to find the parameters which gives the min possible fit value
above is the fit function
R(Tn) and I(Tn) is the true data
Rn^(k) and In^(k) are the variables .
Rn^(k) and In^(k) are generated from another function which is as follows
function [Z, phase] = modelMT(resistivities, thicknesses,frequency)
Rn^(k) - real(Z);
In^(k) - imag(Z);
it takes set of resistivities and thicknesses , i need to choose these values for which i get the min of fit function .
3 Comments
Samar Kenkre
on 16 Jun 2015
I have a very similar scenario and posted my question about an hour ago. Will let u know if I get any hits.
Answers (1)
Alan Weiss
on 16 Jun 2015
I am not completely sure, but it appears that you are trying to minimize a sum of squares. If so, then take a look at lsqnonlin in Optimization Toolbox.
It is often the case that such problems have multiple local solutions. If you want to try to find a global solution, then look at this documentation section using Global Optimization Toolbox.
Alan Weiss
MATLAB mathematical toolbox documentation
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