Non Linear curve fitting
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Hi,
I have an equation of the following form.
Y = K1 * (( x1 - (K2*x2) + (K3*x3)) * (x4 - x2))
x1 is fixed at 1.5. The models accounts for behavior in a nonlinear region. Its a current equation which has a slight nonlinear behavior.
The points I have are the following.. x4 varies from 0.51 - 0.6 and for each x4 I have x3 varying from a nominal value +/- 75mV. The nominal value of x3 will be different for different x4. And again for each x3+/- 75mV I have x2 varying from 0.25-0.5.
Essentially there are two nested loops. x2 always runs from 0.25-5 for every x3+/-75mV for every x4 between 0.51 - 0.6 .
Since I will have a Y for every combination of x2,x3,x4. I read it as a matrix with the input combinations of x2,x3,x4 as say INP and the output Y as a matrix OUT.
Then I used the following to find my coefficients.
Z = (INP' * INP ) \ (INP' * OUT )
The error I am getting is around 15% but I want to have less than 5% error. Could someone please help me in this?
Thanks in advance for the help.
Thanks, Venkat
1 个评论
Venkatesa
2011-8-31
回答（1 个）
Walter Roberson
2011-8-31
0 个投票
Sounds like fmincons() might perhaps be suitable for this, but if you have the curvefitting toolbox or optimization toolbox then there are more specific tools there.
2 个评论
Venkatesa
2011-8-31
Walter Roberson
2011-8-31
Saying that "x4 varies from 0.51 - 0.6" is a constraint on x4; likewise you have a constraint on x2 I think (I might be misreading.) You might be able to program some of the other constraints through the A*x<=b parameter to fmincon() -- if not exactly then perhaps close enough as to meaningfully reduce the search domain.
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