How to use fminsearch for least square error minimization?
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Muhammad Affan Arif
il 25 Lug 2021
Commentato: Muhammad Affan Arif
il 24 Ago 2021
Hi everyone,
I am doing a Modal Parameter Estimation problem. I have measured values, and a function for numerical values. There is an error, which I need to minimize. But when I use fminsearch, it says that the dimensions on left hand side don't agree with that of right hand side. Becuase, fminsearch only gives 1x2, while the error (objective function) is 1x269.
I have used the following MATLAB commands:
e=@(uk) (abs(data_1(2561:2819,4))-abs((2i.*Hr.*uk(2).*uk(1).*uk(1))./(((uk(1).^2)-(ws.^2) + 2i.*uk(2).*uk(1).*ws))).^2
fminsearch(e,[413.4,0.0034])
Here, ws = 400:0.155:440
Any suggestions? Thank you for your time.
2 Commenti
Rik
il 25 Lug 2021
You need to design a function that returns a scalar. Then fminsearch will adjust the starting guesses to minimize that function.
Risposta accettata
Rik
il 26 Lug 2021
Modificato: Rik
il 27 Lug 2021
I mean your objective function must only return 1 value, regardless of the shape of your data.
This is the standard ordinary least squares cost function. You need to provide a handle to your function, your beta will be determined by fminsearch, and you need to know the true value.
t=linspace(0,2*pi,100);
f=@(beta) sin(beta(1)*t+beta(2));
initial_guess=[1 1];
y_true=linspace(0,10,100);
OLS=@(f,beta,y_true) sum((f(beta)-y_true).^2,'all');
beta_fitted=fminsearch(@(beta) OLS(f,beta,y_true),initial_guess)
Edit: sorry, I missed the squared part of the OLS.
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