skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: A Twin Memristor Synapse for Spike Timing Dependent Learning in Neuromorphic Systems

Abstract

Neuromorphic systems consist of a framework of spiking neurons interconnected via plastic synaptic junctures. The discovery of a two terminal passive nanoscale memristive device has spurred great interest in the realization of memristive plastic synapses in neural networks. In this work, a synapse structure is presented that utilizes a pair of memristors, to implement both positive and negative weights. The working scheme of this synapse as an electrical interlink between neurons is explained, and the relative timing of their spiking events is analyzed, which leads to a modulation of the synaptic weight in accordance with the spike-timing-dependent plasticity (STDP) rule. A digital pulse width modulation technique is proposed to achieve these variable changes to the synaptic weight. The synapse architecture presented is shown to have high accuracy when used in neural networks for classification tasks. Lastly, the energy requirement of the system during various phases of operation is presented.

Authors:
 [1];  [1];  [1]; ORCiD logo [2];  [3];  [3]
  1. University of Tennessee (UT)
  2. ORNL
  3. Georgia Institute of Technology
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1492171
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: IEEE International System-on-Chip Conference (SOCC) - Arlington, Virginia, United States of America - 9/4/2018 4:00:00 AM-9/7/2018 4:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Adnan, Md Musabbir, Sayyaparaju, Sagarvarma, Rose, Garrett, Schuman, Catherine D., Woong Ku, Bon, and Kyu Lim, Sung. A Twin Memristor Synapse for Spike Timing Dependent Learning in Neuromorphic Systems. United States: N. p., 2019. Web. doi:10.1109/SOCC.2018.8618553.
Adnan, Md Musabbir, Sayyaparaju, Sagarvarma, Rose, Garrett, Schuman, Catherine D., Woong Ku, Bon, & Kyu Lim, Sung. A Twin Memristor Synapse for Spike Timing Dependent Learning in Neuromorphic Systems. United States. doi:10.1109/SOCC.2018.8618553.
Adnan, Md Musabbir, Sayyaparaju, Sagarvarma, Rose, Garrett, Schuman, Catherine D., Woong Ku, Bon, and Kyu Lim, Sung. Tue . "A Twin Memristor Synapse for Spike Timing Dependent Learning in Neuromorphic Systems". United States. doi:10.1109/SOCC.2018.8618553. https://www.osti.gov/servlets/purl/1492171.
@article{osti_1492171,
title = {A Twin Memristor Synapse for Spike Timing Dependent Learning in Neuromorphic Systems},
author = {Adnan, Md Musabbir and Sayyaparaju, Sagarvarma and Rose, Garrett and Schuman, Catherine D. and Woong Ku, Bon and Kyu Lim, Sung},
abstractNote = {Neuromorphic systems consist of a framework of spiking neurons interconnected via plastic synaptic junctures. The discovery of a two terminal passive nanoscale memristive device has spurred great interest in the realization of memristive plastic synapses in neural networks. In this work, a synapse structure is presented that utilizes a pair of memristors, to implement both positive and negative weights. The working scheme of this synapse as an electrical interlink between neurons is explained, and the relative timing of their spiking events is analyzed, which leads to a modulation of the synaptic weight in accordance with the spike-timing-dependent plasticity (STDP) rule. A digital pulse width modulation technique is proposed to achieve these variable changes to the synaptic weight. The synapse architecture presented is shown to have high accuracy when used in neural networks for classification tasks. Lastly, the energy requirement of the system during various phases of operation is presented.},
doi = {10.1109/SOCC.2018.8618553},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {1}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: