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Implementation of new superconducting neural circuits using coupled SQUIDs

Content Provider	IEEE Xplore Digital Library
Author	Mizugaki, Y. Nakajima, K. Sawada, Y. Yamashita, T.
Copyright Year	2002
Abstract	A novel superconducting neuron circuit and two types of variable synapses, which are based on superconducting quantum interferometer devices (SQUIDs), are presented. A neuron circuit with good input-output isolation and steep threshold characteristics is accomplished using a combination of a single-junction SQUID coupled to a double-junction SQUID. The quantum state of the single-junction SQUID represents the neuron state, and the output voltage of the double-junction SQUID, which is operated in a nonlatching mode with shunt resistors, is a sigmoid-shaped function of the input. Both variable synapse circuits are composed of multiple shunted double-junction SQUIDs. The first type changes its conductance value by using both superconducting and voltage states. The second variable synapse circuit changes its output current digitally by switching its bias currents. Besides numerical simulations of the circuit characteristics, we have fabricated superconducting neural chips in a Nb/AlO/sub x//Nb Josephson junction technology. The fundamental operation of each element and a 2-bit neural-based A/D converter have been successfully tested. A learning system with a variable synapse is also discussed.<>
Sponsorship	Council on Superconductivity Appl. Superconductivity Conference Inc MIT
Starting Page	1
Ending Page	8
Page Count	8
File Size	724477
File Format	PDF
ISSN	10518223
Volume Number	4
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Coupling circuits SQUIDs Neurons Josephson junctions Voltage Niobium Superconducting devices Resistors Switching circuits Numerical simulation
Content Type	Text
Resource Type	Article
Subject	Condensed Matter Physics Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering

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