Theory of a superconducting artificial neuron for extended backpropagation learning algorism - Katayama, Haruna; Fujii, Toshiyuki; Hatakenaka, Noriyuki (International Journal of Engineering and Technology, 2018)
An artificial neuron using superconducting devices, so-called double SQUID, applicable to the extended backpropagation learning algorism is studied. It is shown that the tunable slope of the sigmoid function required in the algorism can be achieved under the fixed temperature by externally applied magnetic fields threading the ring with two Josephson junctions in the double SQUID.Â Â