How to use fminsearch for least square error minimization?
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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 件のコメント
Rik
2021 年 7 月 25 日
You need to design a function that returns a scalar. Then fminsearch will adjust the starting guesses to minimize that function.
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Rik
2021 年 7 月 26 日
編集済み: Rik
2021 年 7 月 27 日
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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