# How to use narxnet for new set of data?

I trained a narxnet network with 4 inputs and 2 targets for system identification. The training performance (RMS) seems pretty good, but the problem is that I don’t know how to use this net for new set of data. According to the Matlab Help, I should use closed loop form (netc) for doing this:

`netc = closeloop(net);`

view(netc);

[Xs,Xi,Ai,Ts] = preparets(netc,X,{},T);

y = netc(Xs,Xi,Ai);

In this process, the target value (T) is required which doesn’t make sense because target is not available for system identification. How should I use this network for new set of input data while I don’t have target values?

# ANSWER

Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.

1. The best way to solve a problem is to use the **MATLAB** example data with which we are familiar

help nndata

2. It doesn’t make sense to guess at what the delays should be. Find the statistically significant feedback delays indicated by the target autocorrelation function and the statistically significant input delays indicated by the input/target crosscorrelation function. If you don’t have a correlation function algorithm in another toolbox use nncorr. However, it has a bug that yields symmetric crosscorrelations. Therefore you have to combine nncorr(x,t…) with nncorr(t,x,…) as illustrated in many of my posts. Search using

greg narxnet nncorr

3. It doesn’t make sense to use the default datadivision setting…

**SEE COMPLETE ANSWER CLICK THE LINK**