equation solving for experimental data

3 views (last 30 days)
teresa
teresa on 10 Feb 2011
Hi,
I am trying to solve a nonlinear equation (Z(f)) of 4 variables which is the following:
Z=sqrt(((x(1)+x(4)-x(1)*x(2)*x(3)*(2*pi*f)^2)^2+(x(1)*x(2)*x(4)+x(3))^2*(2*pi*f)^2)/(1+x(1)^2*x(2)^2*(2*pi*f)^2))
I've got experimentally 200 pairs of values of Z and f and I would like to find the coeficients x(1), x(2), x(3) and x(4) which introduce the less error into these pairs of values.
Curve fitting seems to work similarly, but I am not sure it will work properly.
Can anybody lend me a hand?
Francesc I. Rillo

Answers (1)

Walter Roberson
Walter Roberson on 10 Feb 2011
It appears that the solution that might perhaps be most suitable for fitting would be,
x(1) = 0
x(4) = 0
x(3) = abs(Z)/(2*Pi*f)
x(2) = 1/ (x(3) * 8*Pi^2 * f^2)
  1 Comment
teresa
teresa on 11 Feb 2011
I am sorry but I do not understand that solution. I have probably not explained myself properly.
I have 200 experimental values of Z and f. If I do what you suggest I would obtain 200 x(3) and x(2). What I want is to find the value of each one of the 'x' that for my experimental values introduces less error.
In other words. I got (Z1,f1),(Z2,f2),... (Z200,f200). If I obtain some fix values of x(1), x(2), x(3) and x(4) and use the equation I can obtain (Z1',f1), (Z2',f2),... (Z200',f200). I want to do Z1-Z1', Z2-Z2', ... Z200-Z200' the closest to 0 as possible using just a single value for each 'x'.
I have been told there is a toolbox in Matlab that can help me, similar to the working way of the 'fsolve' function.

Sign in to comment.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by