Multi-parametric non linear multi-courbe made how to?

(xpost: http://lavag.org/topic/11870-multiparameter-nonlinear-multi-curve-fit/)

There is a model of a physical process formalised in LabVIEW simulation toolkit. It take a set of parameters and product of the dependencies of the observable time. I have an experimental data, dependencies of the observable, but measured time on a real system. I would get all the settings, so that the curves of the model will fit experimental. I have an idea of the initial values of the parameters. Sample data is provided below:

Points are given experimental, the curves are the results of manual editing, using the above template.

There was a curve, it would have been easy. I would have used NonlinearCurveFit.vi and supply with a reference to a model of curve generating VI. What can I do with several curves? I really want to avoid porting the fitting

the Numerical Recipes algorithm. I also want to avoid writing a wrapper (a <->LabVIEW) make a link enters Originlab Origin. I use Matlab, of course, but it will write another wrapper. Is there a quick way to do it, without leaving a LabVIEW?

To do this is to 'stack' your different curves in a single table 1 d and secure them.  Here is an example of editing a * exp(-x/x0) and (1-exp(-x/x0)) at the same time.  Exponentials.vi, I take a unique x and concatenated for f(x,a) tables as well as derivatives of output.  The curve of routine, we does not require x single valued or continued or ordered, etc.  It's just a bunch of data, and as long as you can correctly calculate an assumption for each data point you are well.

Tags: NI Software

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