I have a bunch of test measurements data and a semi-empirical model that has 18 parameters which I have to find so that the model fits my data well. So far I've managed to find and optimise the parameters using Optimisation and Global Optimisation algorithms in MATLAB.
Now I would like to explore different approaches for the parameter estimation. I have read some papers where the approach with NNs is described. I am new to NNs and have no idea if this is even possible.
I would create a two layer network with 18 input and output neurons. I am not sure what kind of transfer function would be appropriate for the problem.
The formula I have to fit and find the parameters look like this:
$ y = D \sin(C \arctan(Bx - E(Bx - \arctan(Bx))))$
This is how my data looks like. How would you create network in MATLAB for this problem? Can you give me some hints and a push in the right direction to tackle this problem?
Thanks in advance.