Using neural network for classification

Hi,

I have used GLCM in matlab to extract some texture features from an image. I did this using:

offsets0=[0 1; -1 1; -1;0, -1 1];
glcms=graycomatrix(img, 'Offset', Offsets0);
stats=graycoprops(glcms, 'all');

figure(2), plot([stats.correlation]) % i repeated this for the Contrast, Homogenity and Energy.

This produces the values:

Homgenity= 0.989 0.1468 0.1144 0.1342

Energy= 0.3366 0.3281 0.3340 0.3296

Contrast= 0.9542 0.9353 0.9474 0.9384

Correlation= 0.9798 0.9699 0.9766 0.9707

I want to use the nnprtool GUI to classify these features however I am unsure how to prepare thesr features for input into the neural network.

Can anyone help me ??

Thanks :)

[Greg Heath]

Insufficient information.

What are the classes?

How many input features per example?

How many input/output examples?