Pseudo Sigmoid Function Generator for a Superconductive Neural Network

A superconductive perceptron, an artificial neural network, has been investigated using single flux quantum (SFQ) stochastic logic. A superconductive pseudo sigmoid function generator that corresponds to an artificial neuron device for the perceptron has been proposed and implemented using an SFQ current comparator and a frequency-to-current converter, which generates current that is proportional to the average input SFQ frequency. A frequency-to-current converter has been implemented using a dc-SQUID voltage driver coupled with a Josephson transmission line. We implemented and tested the pseudo sigmoid function generator using the SRL 2.5 kA/cm
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Nb process. The measured input-output characteristic agreed with the ideal sigmoid function with an average error of 0.063%.