Pattern Recognition with Perceptron

Hi, all

I have six patterns as shown below

A1 = [ -1 -1  1  1 -1 -1 -1;
       -1 -1 -1  1 -1 -1 -1;
       -1 -1 -1  1 -1 -1 -1;
       -1 -1  1 -1  1 -1 -1;
       -1 -1  1 -1  1 -1 -1;
       -1  1  1  1  1  1 -1;
       -1  1 -1 -1 -1  1 -1;
       -1  1 -1 -1 -1  1 -1;
        1  1  1 -1  1  1  1];
B1 = [  1  1  1  1  1  1  1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1  1  1  1  1  1  1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1  1  1  1  1  1  1];
C1 = [ -1 -1  1  1  1  1  1 ;
       -1  1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1 -1;
        1 -1 -1 -1 -1 -1 -1;
        1 -1 -1 -1 -1 -1 -1;
        1 -1 -1 -1 -1 -1 -1;
        1 -1 -1 -1 -1 -1 -1;
       -1  1 -1 -1 -1 -1  1;
       -1 -1  1  1  1  1 -1];
A2 = [ -1 -1 -1  1 -1 -1 -1;
       -1 -1 -1  1 -1 -1 -1;
       -1 -1 -1  1 -1 -1 -1;
       -1 -1  1 -1  1 -1 -1;
       -1 -1  1 -1  1 -1 -1;
       -1  1 -1 -1 -1  1 -1;
       -1  1  1  1  1  1 -1;
       -1  1 -1 -1 -1  1 -1;
       -1  1 -1 -1 -1  1 -1];
B2 = [  1  1  1  1  1  1 -1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1  1  1  1  1  1 -1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1  1;
        1  1  1  1  1  1 -1];
C2 = [ -1 -1  1  1  1 -1 -1;
       -1  1 -1 -1 -1  1 -1;
        1 -1 -1 -1 -1 -1  1;
        1 -1 -1 -1 -1 -1 -1;
        1 -1 -1 -1 -1 -1 -1;
        1 -1 -1 -1 -1 -1 -1;
        1 -1 -1 -1 -1 -1  1;
       -1  1 -1 -1 -1  1 -1;
       -1 -1  1  1  1 -1 -1];

I have to recognize these patterns with artificial neural network.

I am new in Matlab. Please help!

I need to divide this data into 2 groups.

The first group A1, B1, C1 as training data. The second group A2, B2, C2 used to validate/test the network.

Example : if I select A1 then the output must display 'A', if I select B1 then the output must display 'B', if I select A2 then the output must display 'A'.

. . # # . . .   
. . . # . . .   
. . . # . . .   
. . # . # . .   
. . # . # . .   => This pattern should be recognized as A
. # # # # # .   
. # . . . # .   
. # . . . # .   
# # # . # # #

In result program, we must explain how to get that. it mean we must explain epochs from start to finish. And Learning Rate = 1 And Threshold Value = 0.5

How do I do that?

Thanks in advance!

Network type is perceptron

[Greg Heath]

Hmm, I submitted an answer to this. Must have made a mistake. Sorry, cannot get back to it until later.

Bottom line was you need a huge amount of input variable reduction.

Greg

[anjanaa subramaniam]

Please help with this code