Analysis of Dynamic Linear and Non-Linear Memristor Device Models for Emerging Neuromorphic Computing Hardware Design

Abstract

The value memristor devices offer to the neuromorphic computing hardware design community rests of the ability to provide effective device models that can enable large scale integrated computing architecture application simulations. Therefore, it is imperative to develop practical, functional device models of minimum mathematical complexity for fast, reliable, and accurate computing architecture technology design and simulation. To this end, various device models have been proposed in the literature seeking to characterize the physical electronic and time domain behavioral properties of memristor devices. In this work, we analyze some promising and practical non-quasi-static linear and non-linear memristor device models for neuromorphic circuit design and computing architecture simulation.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2011
Accession Number
ADA549425

Entities

People

  • Bryant T. Wysocki
  • Nathan McDonald
  • Peter J. Rozwood
  • Robinson E. Pino

Organizations

  • Air Force Research Laboratory

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Artificial Intelligence
  • Boundaries
  • California
  • Computer Architecture
  • Computing System Architectures
  • Experimental Data
  • Memristors
  • Military Research
  • Neural Networks
  • Phase Shift
  • Resistance
  • Simulations
  • Time Domain
  • United States
  • United States Government

Readers

  • Computational Fluid Dynamics (CFD)
  • Integrated Circuit Design and Technology.
  • Systems Analysis and Design

Technology Areas

  • Microelectronics