Affiliation:
1. Institute of Solid State Physics, Russian Academy of Sciences
2. Moscow Institute of Physics and Technology
3. National University of Science and Technology MISiS
Abstract
The artificial neuron proposed earlier for use in superconducting neural networks is experimentally studied. The fabricated sample is a single-junction interferometer, part of the circuit of which is shunted by an additional inductance, which is also used to generate an output signal. A technological process has been developed and tested to fabricate a neuron in the form of a multilayer thin-film structure over a thick superconducting screen. The transfer function of the fabricated sample, which contains sigmoid and linear components, is experimentally measured. A theoretical model is developed to describe the relation between input and output signals in a practical superconducting neuron. The derived equations are shown to approximate experimental curves at a high level of accuracy. The linear component of the transfer function is shown to be related to the direct transmission of an input signal to a measuring circuit. Possible ways for improving the design of the sigma neuron are considered.
Publisher
The Russian Academy of Sciences