Energy efficient Ferroelectric Field Effect Transistor based oscillators for neuromorphic system design

Research output: Contribution to journalArticle

Abstract

Neuromorphic or bioinspired computational platforms, as an alternative for von-Neumann structures, have benefitted from the excellent features of emerging technologies in order to emulate the behaviour of biological brain in an accurate and energy efficient way. Integrability with CMOS technology and low power consumption make Ferroelectric FET (FEFET) an attractive candidate to perform such paradigms, particularly for image processing. In this paper, we use FEFET device to make energy-efficient oscillatory neurons as main parts of neural networks for image processing applications, especially for edge-detection. Based on our simulation results, we estimated a significant energy efficiency compared to other technologies which shows roughly 5 -120 × reduction, depended on the design.

Original languageEnglish
JournalIEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Early online date29 Sep 2020
DOIs
Publication statusE-pub ahead of print - 29 Sep 2020

Keywords

  • CMOS Technology
  • Coupled Oscillator
  • Energy efficiency
  • FEFET Device
  • Frequency Modulation
  • Frequency modulation
  • Hysteresis
  • Image processing
  • Integrated circuit modeling
  • Neuromorphic Computing
  • Neurons
  • Oscillators

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