Hopfield Networks (HN)

A Hopfield network (HN) is a network where every neuron is connected to every other neuron.
Each node is input before training, then hidden during training and output afterwards. The networks are trained by setting the value of the neurons to the desired pattern after which the weights can be computed. The weights do not change after this. Once trained for one or more patterns, the network will always converge to one of the learned patterns because the network is only stable in those states.