Least square fitting - lsqcurvefit - multiple equations - not enough input arguments -

1 次查看（过去 30 天）

显示更早的评论

Mohammad Aljarrah 2020-5-17

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/526210-least-square-fitting-lsqcurvefit-multiple-equations-not-enough-input-arguments

评论： Mohammad Aljarrah 2020-5-18

采纳的回答： Ameer Hamza

在 MATLAB Online 中打开

Hello everyone,

I am trying to fit some experimental data to a cerain model,

my data:

x_exp = [0.109112654
174029442
2775686
442708583
706098923
126193863
796225113
864892769
569366345
28791982
];
y_exp = [5247.044317
755912
15367
43738
90041
48525
24278
30828
140804.9657
207196.2571
];

i want to fit this data using lsqcurvefit, but the problem is my model is not a one line code, it is contructed as follows, it has 4 parameters, o is the variable and my final output is G, i want to fit my y_exp with G:

% parameters are k , tau , Gg , G0
A = (o*tau)^-k * cos (k*pi/2);
B = (o*tau)^-k * sin (k*pi/2);
G1 = G0 + (((Gg-G0)* (1+A))/ (((1+A)^2)+B^2));
G2 = ((Gg-G0)* (-B)/ (((1+A)^2)+B^2));
G = ((G1^2 + G2^2)^0.5);

when i used lsqcurvefit, i constructed the code as follows, but i keep getting a message (Not enough input arguments):

% define A & B
A = @(x,xdata)(xdata*x(2))^-x(1) * cos (x(1)*pi/2);
B = @(x,xdata)(xdata*x(2))^-x(1) * sin (x(1)*pi/2);
% Define G' & G''
G1 = @(x,xdata)x(4) + (((x(3)-x(4))* (1+A(x)))/ (((1+A(x))^2)+B(x)^2));
G2 = @(x,xdata)((x(3)-x(4))* (-B(x))/ (((1+A(x))^2)+B(x)^2));
% Define G
G = @(x,xdata)((G1(x)^2 + G2(x)^2).^0.5);
x0 = [0.5 1E-4 1E+7 1E-5];
[x,resnorm,~,exitflag,output] = lsqcurvefit(G,x0,x_exp,y_exp)

can any one please help me with this?

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Ameer Hamza 2020-5-17

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/526210-least-square-fitting-lsqcurvefit-multiple-equations-not-enough-input-arguments#answer_433015

在 MATLAB Online 中打开

There are few errors in writing the equations. Following code correct those

A = @(x,xdata)(xdata*x(2)).^-x(1) * cos (x(1)*pi/2);
B = @(x,xdata)(xdata*x(2)).^-x(1) * sin (x(1)*pi/2);
% Define G' & G''
G1 = @(x,xdata)x(4) + (((x(3)-x(4))* (1+A(x,xdata)))./(((1+A(x,xdata)).^2)+B(x,xdata).^2));
G2 = @(x,xdata)((x(3)-x(4))* (-B(x,xdata))./(((1+A(x,xdata)).^2)+B(x,xdata).^2));
% Define G
G = @(x,xdata)((G1(x,xdata).^2 + G2(x,xdata).^2).^0.5);
x0 = [0.5 1E-4 1E+7 1E-5];
[x,resnorm,~,exitflag,output] = lsqcurvefit(G,x0,x_exp,y_exp)

However, now the issue is that lsqcurvefit converges to a wrong output, which is not optimal. Are you sure your model is correct?

7 个评论
显示 5更早的评论隐藏 5更早的评论

Ameer Hamza 2020-5-18

The solution posted by Alex is calculated using another optimization package, called 1stOpt. That is different software, so MATLAB code cannot be used in that.

Mohammad Aljarrah 2020-5-18