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Title: Three-terminal ferroelectric synapse device with concurrent learning function for artificial neural networks

Abstract

Spike-timing-dependent synaptic plasticity (STDP) is demonstrated in a synapse device based on a ferroelectric-gate field-effect transistor (FeFET). STDP is a key of the learning functions observed in human brains, where the synaptic weight changes only depending on the spike timing of the pre- and post-neurons. The FeFET is composed of the stacked oxide materials with ZnO/Pr(Zr,Ti)O{sub 3} (PZT)/SrRuO{sub 3}. In the FeFET, the channel conductance can be altered depending on the density of electrons induced by the polarization of PZT film, which can be controlled by applying the gate voltage in a non-volatile manner. Applying a pulse gate voltage enables the multi-valued modulation of the conductance, which is expected to be caused by a change in PZT polarization. This variation depends on the height and the duration of the pulse gate voltage. Utilizing these characteristics, symmetric and asymmetric STDP learning functions are successfully implemented in the FeFET-based synapse device by applying the non-linear pulse gate voltage generated from a set of two pulses in a sampling circuit, in which the two pulses correspond to the spikes from the pre- and post-neurons. The three-terminal structure of the synapse device enables the concurrent learning, in which the weight update can be performedmore » without canceling signal transmission among neurons, while the neural networks using the previously reported two-terminal synapse devices need to stop signal transmission for learning.« less

Authors:
; ; ;  [1];  [2]
  1. Advanced Technology Research Laboratories, Panasonic Corporation, Seika, Kyoto 619-0237 (Japan)
  2. Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Wakamatsu-ku, Kitakyushu 808-0196 (Japan)
Publication Date:
OSTI Identifier:
22089250
Resource Type:
Journal Article
Journal Name:
Journal of Applied Physics
Additional Journal Information:
Journal Volume: 111; Journal Issue: 12; Other Information: (c) 2012 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0021-8979
Country of Publication:
United States
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; ASYMMETRY; DENSITY; FERROELECTRIC MATERIALS; FIELD EFFECT TRANSISTORS; FILMS; MODULATION; NEURAL NETWORKS; OXYGEN COMPOUNDS; PLASTICITY; POLARIZATION; PZT; RUTHENIUM COMPOUNDS; SAMPLING; STRONTIUM COMPOUNDS; SYMMETRY; TRANSMISSION; ZINC OXIDES

Citation Formats

Nishitani, Y., Kaneko, Y., Ueda, M., Fujii, E., and Morie, T. Three-terminal ferroelectric synapse device with concurrent learning function for artificial neural networks. United States: N. p., 2012. Web. doi:10.1063/1.4729915.
Nishitani, Y., Kaneko, Y., Ueda, M., Fujii, E., & Morie, T. Three-terminal ferroelectric synapse device with concurrent learning function for artificial neural networks. United States. doi:10.1063/1.4729915.
Nishitani, Y., Kaneko, Y., Ueda, M., Fujii, E., and Morie, T. Fri . "Three-terminal ferroelectric synapse device with concurrent learning function for artificial neural networks". United States. doi:10.1063/1.4729915.
@article{osti_22089250,
title = {Three-terminal ferroelectric synapse device with concurrent learning function for artificial neural networks},
author = {Nishitani, Y. and Kaneko, Y. and Ueda, M. and Fujii, E. and Morie, T.},
abstractNote = {Spike-timing-dependent synaptic plasticity (STDP) is demonstrated in a synapse device based on a ferroelectric-gate field-effect transistor (FeFET). STDP is a key of the learning functions observed in human brains, where the synaptic weight changes only depending on the spike timing of the pre- and post-neurons. The FeFET is composed of the stacked oxide materials with ZnO/Pr(Zr,Ti)O{sub 3} (PZT)/SrRuO{sub 3}. In the FeFET, the channel conductance can be altered depending on the density of electrons induced by the polarization of PZT film, which can be controlled by applying the gate voltage in a non-volatile manner. Applying a pulse gate voltage enables the multi-valued modulation of the conductance, which is expected to be caused by a change in PZT polarization. This variation depends on the height and the duration of the pulse gate voltage. Utilizing these characteristics, symmetric and asymmetric STDP learning functions are successfully implemented in the FeFET-based synapse device by applying the non-linear pulse gate voltage generated from a set of two pulses in a sampling circuit, in which the two pulses correspond to the spikes from the pre- and post-neurons. The three-terminal structure of the synapse device enables the concurrent learning, in which the weight update can be performed without canceling signal transmission among neurons, while the neural networks using the previously reported two-terminal synapse devices need to stop signal transmission for learning.},
doi = {10.1063/1.4729915},
journal = {Journal of Applied Physics},
issn = {0021-8979},
number = 12,
volume = 111,
place = {United States},
year = {2012},
month = {6}
}