Fully digital neural network implementation based on pulse density modulation

An efficient implementation of a Hopfield-type fully connected neural-network architecture is presented that is based on a pulse-density modulation technique implemented by using fully digital structures. The synaptic weights are programmable, and thus the area of one synapse and the entire network depends on the resolution of the weight. Advantages of the design are its modularity and expandability