Matrix with unknown values

Dear community, I am loosing my mind with this simple problem:

A = B .* X

where A and B are two arrays [3x1x80] and X is a matrix [3x3x80].

As X has 5 unknown values I tried to implement this matrix equation with fminsearch:

 function [estimates,model] = findvalues(A,B)

 X0 = [0.1 0.1 0.2 0.3 0.56];
 model = @maps;
 options=optimset('Display','off','MaxIter',100000,'MaxFunEvals',100000,'TolX',1e-8);
 [estimates] = fminsearch(model, X0, options);
 function [ FittedCurve,sse] = maps(params)
 X = zeros(3,3,80); 

        a = params(1);
        b = params(2);
        c = params(3);
        d = params(4);
        e = params(5);

        X(1,1,:) = -(Rb + (1 ./ a));
        X(1,2,:) = (1 ./ b) - (((e - (1 - f)) ./ f) ./ (V ./ f) .* (1 ./ c));
        X(2,1,:) = (1 ./ a);        
        c = -(((r1o .* CRo) + R1o0) + (1 ./ b));
        X(2,2,:) = c';
        X(2,3,:) = (1 ./ c);
        X(3,2,:) = (1 ./ b) - ((d./(V.*(1-h))).*(1./a));
        X(3,3,:) = (-(Ri + (1 ./ c)));
for i = 1:80
    FittedCurve(:,:,i) = mtimes( ((sin(a) .* (I - ((exp(X(:,:,i))).^TR))) , B);
end                

            ErrorVector = FittedCurve - A;   
            sse = sum((ErrorVector .^ 2),3);
    end
    end

It does not work. Is it because maybe fminsearch is not the most suitable function for this problem? Or is there a conceptual mistake?

I really thank you for the support.

[Jan]

Please fix:

 A and X are two arrays [3x1x80] and X is a matrix [3x3x80].

One of the matrices is B.

Please explain "in does not work" with any details. It is easier to suggest a solution than to guess the problem.

[Marianna]

Thank you. I get this error:

 Assignment has more non-singleton rhs dimensions than non-singleton subscripts

 Error in fminsearch (line 200)
 fv(:,1) = funfcn(x,varargin{:});

 Error in findvalues (line 17)
 [estimates] = fminsearch(model, start_point, options);

Answer 1

[Walter Roberson]

Your function must return a scalar to be used with fminsearch. You have 3D array A so ErrorVector is 3D and you sum() the square of that over the 3rd dimension, which is going to give you a 2D array instead of a scalar.

[Marianna]

I tried with the mean of the error vector and it works now.

Thank you so much.

Do you think that the mean could be a solution?

[Walter Roberson]

No, I think the solution is

sse = sum(ErrorVector(:) .^ 2);

[Marianna]

Ok. Thank you.