Pulse-stream arithmetic in programmable neural networks

A pulse-stream signaling mechanism is described that is analogous to that found in natural neural systems. Previous work has resulted in the development of synthetic neural networks implemented as VLSI devices using pulse streams to represent neural states and a time-chopping technique to implement multiplication by synaptic weights. Synaptic weights are stored on-chip in digital memory. An alternative method for representing synaptic weights is described which uses dynamic storage capacitors to hold the charge proportional to synaptic weight. The capacitive storage devices are refreshed from off-chip digital RAM via a digital-to-analog converter. The presence, absence, and rate of pulse firing of the neuron are used to represent its state. Multiplication of a neuron state by a synaptic weight is performed by modifying the width of individual pulses passing through the synapse. A circuit that performs this function is described. The small synaptic circuit that results allows relatively high levels of integration in comparison to other programmable silicon neural forms.<<ETX>>