How to create Neural Network classifier for pattern Recognition ?

I want to create a Neural network with 50 thousand nodes for EEG recognition . Can anybody help me to do this?

Answer 1

[Greg Heath]

How many classes/categories? c = ?

What is the dimensionality of your input vectors? I= ?

How many input/target examples do you have? N = ?

Choose the output target vectors to be O = c dimensional unit column vectors with a 1 in the row corresponding to the class index.

 [ I N ] = size(input)  % = ?
 [ O N ] = size(target) % = ?

Using defaults,

 Ntrn   = N - 2*round(0.15*N) % No. of training examples
 Ntrneq = Ntrn*O              % No. of training equations
 H      = 10                  % No. of hidden layer nodes
 Nw     = (I+1)*H+(H+1)*O     % No of unknown weights

Is Ntrneq > Nw ?

Is Ntrneq >> Nw ?

Use the help and doc commands and try one or more of the following practice examples

   simpleclass_dataset   - Simple pattern recognition dataset.
   cancer_dataset        - Breast cancer dataset.
   crab_dataset          - Crab gender dataset.
   glass_dataset         - Glass chemical dataset.
   iris_dataset          - Iris flower dataset.
   ovarian_dataset       - Ovarian cancer dataset.
   thyroid_dataset       - Thyroid function dataset.
   wine_dataset          - Italian wines dataset.

Search for more info and examples in the NEWSGROUP and ANSWERS using

 greg patternnet

Hope this helps.

Thank you for formally accepting my answer

Greg

[moahaimen talib]

dear sir i need your help i need some explaining of using nn for character recognition i have 20 images to read and i must recognize 20 character of them could please help me

Answer 2

[Shashank Prasanna]

Here is a walk through example of how to do pattern classification using the Neural Network Toolbox:

http://www.mathworks.com/help/nnet/gs/classify-patterns-with-a-neural-network.html

Feel free to go through the other examples in the documentation as well.