The Circuit Realization of a Neuromorphic Computing System with Memristor-Based Synapse Design

Abstract

Conventional CMOS technology is slowly approaching its physical limitations and researchers are increasingly utilizing nanotechnology to both extend CMOS capabilities and to explore potential replacements. Novel memristive systems continue to attract growing attention since their reported physical realization by HP in 2008. Unique characteristics like non-volatility, re-configurability, and analog storage properties make memristors a very promising candidate for the realization of artificial neural systems. In this work, we propose a memristor-based design of bidirectional transmission excitation/inhibition synapses and implement a neuromorphic computing system based on our proposed synapse designs. The robustness of our system is also evaluated by considering the actual manufacturing variability with emphasis on process variation.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2013
Accession Number
ADA585221

Entities

People

  • Beiye Liu
  • Bryant Wysocki
  • Tingwen Huang
  • Yiran Chen

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Capacitance
  • Character Recognition
  • Circuits
  • Computers
  • Content Addressable Memory
  • Energy Consumption
  • Excitation
  • Inhibition
  • Memristors
  • Neural Networks
  • Pattern Recognition
  • Recognition
  • Simulations
  • Standards
  • Synapses

Fields of Study

  • Computer science

Readers

  • Integrated Circuit Design and Technology.
  • Oncology

Technology Areas

  • Biotechnology