problem using fsolve in parameter identification, is it good to add redundancy?

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Fan
Fan 2013-2-3
I want to identify 4 parameters of a nonlinear equations f(x,y)=0. Now I got several groups of experimental data: x and y.
Theoretically, only four groups of x and y is needed to create 4 equations to solve and get the 4 parameters.
But is it better for me to use all the groups of x and y as redundancy in fsolve so that I can get a better identification result? How does fsolve works?

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Shashank Prasanna
fsolve in some sense tries to force the sum of squares of the output of system to zero. If you have a system of non-linear equations then use FSOLVE. Redundant equations will feature in the optimization during the minimization as well.
On the other hand if you have a single nonlinear equation with 4 parameters and several observations (groups of x and y) and would like to estimate the 4 parameters then use lsqnonlin or nlinfit. Can you give us an idea or an example of your f(x,y)
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