Energy-efficient ferroelectric field-effect transistor-based oscillators for neuromorphic system design

Hossein Eslahi*, Tara J. Hamilton, Sourabh Khandelwal

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
50 Downloads (Pure)


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 behavior of the biological brain in an accurate and energy-efficient way. Integrability with CMOS technology and low power consumption make ferroelectric field-effect transistor (FEFET) an attractive candidate to perform such paradigms, particularly for image processing. In this article, we use the FEFET device to make energy-efficient oscillatory neurons as the 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 with other technologies, which shows roughly 5−120× reduction, depending on the design.

Original languageEnglish
Pages (from-to)122-129
Number of pages8
JournalIEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Issue number2
Early online date29 Sept 2020
Publication statusPublished - Dec 2020

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