Use of a persistent photoconductive array in the learning of an optoelectronic neural processor

Persistent photoconductors of npnp doping-modulated amorphous silicon multilayers are investigated for the implementation of variable analog and nonvolatile synaptic weights of an optoelectronic neural processor. The time dependence of the persistent photoconductance of the amorphous silicon multilayers is characterized in experiments. The learning performance of an optical pattern classifier with the persistent photoconductive array is analyzed by computer simulations.