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 # load in the data
  initData();

 # train the network
    for(my $j = 0;$j <= $numEpochs;$j++)
    {

        for(my $i = 0;$i<$numPatterns;$i++)
        {

            #select a pattern at random
            $patNum = (rand()*$numPatterns)-0.001;

            #calculate the current network output
            #and error for this pattern
            calcNet();

            #change network weights
            WeightChangesHO();
            WeightChangesIH();
        }