Analysis of Optoelectronic Neural Networks with Persistent Photoconductors Array

잔류 광전도체 어레이를 이용한 광전신경망의 학습성능분석

An optoelectronic implementation of analog and non-volatile synaptic weights of neural networks is proposed by using the doping modulated amophous silicon multilayer. The persistent photoconductivity(PPC) of the multilayer induced by a short illumination is characterized in experiment and implemented to the non-volatile synaptic weights. An optoelectronic processor with the single layer perceptron algorithm is also proposed. Some learning equations of the processor and the results of simulation are presented.