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

1 vue (au cours des 30 derniers jours)
Hello everyone,
I am trying to fit some experimental data to a cerain model,
my data:
x_exp = [0.109112654
0.174029442
0.2775686
0.442708583
0.706098923
1.126193863
1.796225113
2.864892769
4.569366345
7.28791982
];
y_exp = [5247.044317
8170.755912
12604.15367
19261.43738
29160.90041
42700.48525
63815.24278
95016.30828
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?

Réponse acceptée

Ameer Hamza
Ameer Hamza le 17 Mai 2020
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 commentaires
Ameer Hamza
Ameer Hamza le 18 Mai 2020
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
Mohammad Aljarrah le 18 Mai 2020
gotcha. thank you very much for clearing that out. i really appreciate your time and efforts.

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