how do i optimize weights of neural network using GA in MATLAB

When, 

 [ I N ] = size(input)
 [ O N ] = size(target)
  MSE00  = mean(var(target',1))% Reference MSE

 The number of available training equations is

Ntrneq = N*O

 For an I-H-O node topology the number of unknown weights is

Nw = (I+1)*H+(H+1)*O = (I+O+1)*H+1

 Obviously, 

 1. The "3" in the GA input is replaced by I+O+1

 2. The normalized mse calculation is

     NMSE = mean((target(:)-output(:)).^2)/MSE00

Of course there will be more complications if the performance measure has to be decomposed into class and trn/val/tst subsets.