We have previously reported on a feed forward neural network designed to identify the charge and momentum of muons in the forward trigger system of the ATLAS detector. The network was found to produce an unbiased estimate of the particles momenta and charges. Here we report on further developments, mainly in optimizing the preprocessing of the input to the network, and on the comparison between the performance of the network and the first level muon-trigger.