Neural networks using bit stream arithmetic: a space efficient implementation

In this paper an expandable digital architecture that provides an efficient implementation base for large neural networks, is presented. The architecture uses the circuit for arithmetic operations on delta encoded signals to carry out the large number of required parallel synaptic calculations. All real valued quantities are encoded on delta bit streams. The actual digital circuitry is simple and highly regular, thus allowing very efficient space usage of fine grained FPGAs