Artificial neural network circuits with Josephson devices

Conference · Fri Mar 01 00:00:00 EST 1991 · IEEE Transactions on Magnetics (Institute of Electrical and Electronics Engineers); (United States)

OSTI ID:6088506

Harada, Y; Goto, E ^[1]

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1. Quantum Magneto-Flux Logic Project, ERATO, Research Development Corp. of Japan, I-280 Higashi-Koigakubo, Kokubunji, Tokyo 185 (JP)

This article describes a new approach of Josephson devices for computer applications. With an artificial neural network scheme Josephson devices is expected to develop a new paradigm for future computer systems. Here the authors discuss circuit configuration for a neuron with Josephson devices. The authors proposed a combination of a variable bias source and Josephson devices for a synapse circuit. The bias source signal is steered by the Josephson device input signal and becomes the synapse output signal. These output signals are summed up at the specific resistor or inductor to produce the weighted sum of Josephson devices input signals. According to the error signal, the bias source value is corrected. This corresponds to the learning procedure.

• OSTI ID: 6088506
• Report Number(s): CONF-900944-; CODEN: IEMGA
• Journal Information: IEEE Transactions on Magnetics (Institute of Electrical and Electronics Engineers); (United States), Vol. 27:2; Conference: 1990 applied superconductivity conference, Snowmass, CO (United States), 24-28 Sep 1990; ISSN 0018-9464
• Country of Publication: United States
• Language: English

Related Subjects

75 CONDENSED MATTER PHYSICS
SUPERCONDUCTIVITY AND SUPERFLUIDITY
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
COMPUTER NETWORKS
DESIGN
COMPUTERS
MEMORY MANAGEMENT
NEURAL NETWORKS
COMPUTERIZED SIMULATION
SUPERCONDUCTING DEVICES
ARTIFICIAL INTELLIGENCE
JOSEPHSON JUNCTIONS
JUNCTIONS
SIMULATION
SUPERCONDUCTING JUNCTIONS
665412* - Superconducting Devices- (1992-)
990200 - Mathematics & Computers