public void backPropagate(double[] desiredOutput) {
        if(desiredOutput.length != network.get(network.size()-1).size())
            throw new IllegalArgumentException("Invalid number of outputs");

        double outputError = 0;

        //start at output layer
        for(int i = network.size()-1; i > 0; --i) {
            for(int j = 0; j < network.get(i).size(); ++j) {
                Neuron n = network.get(i).get(j);

                //calculate errors
                if(i == network.size()-1) {//output neuron
                    n.setError(activator.fprime(n.getValue()) * (desiredOutput[j] - n.getValue()));
                    outputError += n.getError();
                }
                else {
                    double w = 0;
                    for(Link l : n.forward) { w += l.weight; }
                    n.setError(activator.fprime(n.getValue()) * w * outputError);
                }

                //adjust weights
                for(Link l : n.backward) { l.weight += n.getError() * l.prev.getValue(); }
            }
        }
    }