Hi Siwei
The error is due to lsqcurvefit expecting a function handle as its first input.
Here is a way to modify the code:
- Define FunModel as a separate function or as an anonymous function that accepts the parameters and the independent variable (x) as inputs and returns the dependent variable (J_mod).
- Pass a handle to this function as the first argument to lsqcurvefit.
Here is a code snippet to help you get started:
global Dim_N
Dim_N = 2;
%--------Objective Function (Curve)---------------
x = linspace(1.4,1.9,1000);
J_aim = 0.01./((x-1.6).^2+0.01^2)+0.05./((x-1.7).^2+0.05^2);
plot(x,J_aim);
hold on
%-------Fitting Parameters----------------
gT = [0.5,0.2];
g = transpose(gT);
w = [1.6,0 ; 0, 1.7];
kappa = [0.01,0.05];
%-------Reshape these Parameters----------
para = [gT, kappa, reshape(w,[1,Dim_N^2])];
%-------Initial Gauss---------------------
g0 = [0.3,0.3]; w0 = [1,0; 0, 1]; kappa0 = [0.1, 0.1];
para0 = [g0, kappa0, reshape(w0,[1,Dim_N^2])]; % Fixed to use initial guesses
% Define the model function as an anonymous function
FunModel = @(para,x)modelFunction(para, x);
% Use lsqcurvefit with the function handle
para_opt = lsqcurvefit(FunModel, para0, x, J_aim);
%-------Fitting Model---------------------
function J_mod = modelFunction(para, x)
global Dim_N
gT = para(1:Dim_N);
kappa = para(Dim_N+1:2*Dim_N);
w = zeros(Dim_N);
%-------Reconstruct the w matrix----------
point = 0;
for index = 2*Dim_N+1: length(para)
point = point + 1;
i = fix( (point-1)/Dim_N ) + 1;
j = point - (i-1)*Dim_N;
w(i,j) = para(index);
end
%-------My fitting model "J_mod"----------
J_mod = zeros(1,length(x));
g = transpose(gT);
Ht = w - 0.5i*diag(kappa);
for i=1:length(x)
temp = Ht - x(i)*eye(Dim_N);
J_mod(i) = imag( gT*(temp\g) ); % Corrected to use matrix left division
end
end
