A neural network is one architecture for an optoelectronic signal processor which operates in a dynamic parallel mode. The basic node is a circuit which has multiple inputs and a single output which is in general fanned out to several next stage inputs. A key feature is that an adjustable synaptic weight is applied to each input. Then the weighted inputs are summed and the sum is thresholded to produce a single on/off output signal. A neural network is made up of many such neurodes with a massive number of interconnections. Because of the interconnectivity requirements, it is attractive to use optical signals as the input and output signals to the neurode. Because of the weighting, summing and thresholding requirement it is attractive to use electronic device implementations. Therefore the neural signal processor is a natural candidate for optoelectronic device technology.