CODEWITHSUNDEEP
matlaboptimization
YLM
YLM

Reputation: 345

MATLAB I would like to minimize the difference fitting

I have a curve that looks like an exponentiel function, I would like to fit this curve with this equation :

enter image description here

The goal is to find the value of A, T and d which will minimize V with my initial curve.

I did a function that is able to do it but it takes 10 seconds to run. 3 loops that test all the values that I want to and at the end of the 3 loops I calculate the RMSD (root mean square deviation) between my 2 curves and I put the result in a vector min_RMSN, at the end I check the minimum value of min_RMSD and it's done...

But this is not the best way for sure.

Thank you for your help, ideas :)

Upvotes: 4

Views: 1034

Answers (1)

Mad Physicist
Mad Physicist

Reputation: 114250

Matlab has a built in fminsearch function that does pretty much exactly what you want. You define a function handle that takes the RMSE of your data vs. the function fit, pass in your initial guess for A, T and d, and get a result:

x0 = [A0, T0, d0]
fn = @(x) sum((x(1) * (1 - exp(-x[2] / (t - x[3]))) - y).^2)
V = fminsearch(@fn, x0)

Here t is the x-data for the curve you have, y are the corresponding y-values and, A0, T0, d0 are the initial guesses for your parameters. fn computes the suquare of the RMSE between your ideal curve and y. No need to take the square root since you minimizing the square will also minimize the RMSE itself, and computing square roots takes time.

Upvotes: 1

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