The best Ann configuration

 1. Accept all default parameters except for the number of hidden nodes, H. 
 2. Minimize H subject to the constraint that the degree-of-freedom adjusted 
    mean-square-error of the training data is less than 1% of the average training target variance. 
 3. Design and test Ntrials >= 10 nets for each value of H in a range less than the upper
    bound Hub (determined by not having more unknown weights Nw than training equations Ntrneq).
    The untrained nets only differ by the random trn/val/tst data division AND the random initial weights. 
 4. Rank the nets via their slightly biased performance on validation data. 
 5. Obtain unbiased performance estimates on the nets using test data. 
 6. Statistically significant differences in performance can be estimated using the standard 
    deviation of the performance estimates.

I have posted zillions of examples in both the NEWSGROUP and ANSWERS using the same notation. Therefore searching with

 greg fitnet Ntrials

should dig up enough references to clarify what I have written.