An autoassociative network of polarized dual synapses

The storage rule used in Hopfield networks discards information available in the memory prototype vectors, causing reduced storage capacity and associativity. An analysis of this fundamental effect leads to an alternative network of polarized dual synapses which preserve information about the polarity of the prototype patterns. Ancillary techniques for performance improvement are detailed. Extensive simulations confirm that substantial performance advantages are realized with polarized networks