General optimization (math/fitting/signal analysis)

[Tropo]

I have two signals which I want to make a fit to simultaneously and optimizing the fitting on both. Both function are dependent on 4 input parameters each. In additon there are two input variables which are held constant, and an independent variable X.  The fitting function is attached as a VI (LV 8).

I'm not sure about the best of doing this using the fitting or optimization functions in LabVIEW.

The signals look like this:

[altenbach]

All fitting tools in LabVIEW use double precision, so it is not clear why you have chosen SGL for the parameters and outputs.

In any case, you could simply append the two data arrays for fitting and all the regular nonlinear fitting (VI model) will work. You don't need to wire [X]. See how far you get.

[Tropo]

What do you mean append. Where?  Do you mean build a 2D array?

[altenbach]

You can use "built array" in concatenate mode to generate a 1d array containing both graphs. Similarly, you would also do the same with your data (y input). Nonlinear fit will optimize the parameter set so the two concatenated 1d arrays (data, simulation based on parameters) match best.

(Sorry, posting via phone)

[Tropo]

My problem is that I still get an array as output and not just a single value like in the Optimize Extended Rosenbrock.vi example.

[altenbach]

Use Nonlinear Curve Fit VI instead.