  An artificial neural network algorithm is implemented using a field
programmable gate array hardware. One hidden layer is used in the feed-forward
neural network structure in order to discriminate one class of patterns from
the other class in real time. With five 8-bit input patterns, six hidden nodes,
and one 8-bit output, the implemented hardware neural network makes decision on
a set of input patterns in 11 clocks and the result is identical to what to
expect from off-line computation. This implementation may be used in level 1
hardware triggers in high energy physics experiments
