UID:
(DE-602)gbv_1756585385
Format:
5
ISSN:
1051-8223
Content:
Neuromorphic and bio-inspired circuits have reached considerable attention since Moore's Law is coming to its limitations. Information processing in mammalian brains takes place in a far more energy-efficient manner and significantly faster than in the best computing architecture nowadays. We propose an approach to bring those benefits to a superconducting information processing circuit. Since the computation in a neuronal network is considered as analogue and the computation as digital, the design is grown around a Josephson comparator with its inherent non-linearity in the transfer function as the central information processing unit. Furthermore, a modified version of the Josephson Transmission Line is used to realize an adaptable coupling between neuron cells. This circuit design benefits of the noise in a 4.2 K environment and is therefore more resilient to noise and switching errors than conventional digital circuits. The proposed circuit behavior in a 2-neuron configuration and the integration in a network topology will be investigated.
In:
Institute of Electrical and Electronics Engineers, IEEE transactions on applied superconductivity, New York, NY : Inst., 1991, 31(2021), 5, Seite 1800505, 1051-8223
In:
volume:31
In:
year:2021
In:
number:5
In:
pages:1800505
In:
extent:5
Language:
English
DOI:
10.1109/TASC.2021.3063212
