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How to use fminsearch for least square error minimization?

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Muhammad Affan Arif
Muhammad Affan Arif 2021 年 7 月 25 日
コメント済み: Muhammad Affan Arif 2021 年 8 月 24 日 9:12
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
Muhammad Affan Arif
Muhammad Affan Arif 2021 年 7 月 26 日
@Rik So you mean, I need to design a function that minimizes the objective function at each data point?

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Rik
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)
beta_fitted = 1×2
-0.0000 7.8540
Edit: sorry, I missed the squared part of the OLS.
  1 件のコメント
Muhammad Affan Arif
Muhammad Affan Arif 2021 年 8 月 24 日 9:12
Thank you, very much. It solved my issue.
I apologize for late acknowledgement.

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