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Determine function parameters with neural network

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I am currently studying a doctoral thesis in control theory. At the end of every chapter there is a simulation of a relative-with-the-subject problem. I have finished the theory,but for further understanding I would like to reproduce the simulations. The first simulation is as follows :
The solution of the problem concludes in a system of differential equations whose right hand side consists of functions with unknown parameters. The author states the following :
"We will use neural networks with one hidden layer,sigmoid basis functions and 5 weights in the external layer in order to approximate every parameter of the unknown functions.More specifically, the weights of the hidden layer are selected through iterative trials and are kept stable during the simulation."
And then he states the logic with which he selects the initial values of the unknown parameters and finally shows the results of the simulation.
Could anyone give a guide or links or steps that I need to know in order to solve this specific problem myself in MATLAB? The results of a google search are chaotic since I don't really know what I'm looking for.
If you need any more info,feel free to ask!

Accepted Answer

Greg Heath
Greg Heath on 14 Jul 2014
The function fitnet can be used to model bounded continuous functions given a sufficient number (N) of I-dimensional input/O-dimensional output-target pair examples. For examples see
help fitnet
doc fitnet
help nndatasets
doc nndatasets
Also search for examples in the NEWSGROUP and ANSWERS. For example search
greg fitnet Ntrials
Hope this helps.
Thank you for formally accepting my answer.

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